diff --git "a/Source Code/5. Reranking Algorithm KNN.ipynb" "b/Source Code/5. Reranking Algorithm KNN.ipynb"
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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[{"file_id":"1ZYogLNhD2G2-R5S9dh-e0xpAtnl2-x3H","timestamp":1735482594838},{"file_id":"1FG7ZKNWvY9NzttqgpQZ3lrCo4bBNQfa0","timestamp":1735482435351}],"mount_file_id":"1VDzeZyw5dQEni3I1oSoABOBF7dee8oGv","authorship_tag":"ABX9TyNBkuigfq31ez8SKqrVRusb"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["## Reranking Applying\n","\n"],"metadata":{"id":"12RB1-6TSqjS"}},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","file_path = \"/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Datasets\"\n","files = [\n","    \"australian_user_reviews.json.gz\",\n","    \"australian_users_items.json.gz\",\n","    \"bundle_data.json.gz\",\n","    \"steam_games.json.gz\"\n","]"],"metadata":{"id":"ndVraj2XhD0Y","executionInfo":{"status":"ok","timestamp":1735799867719,"user_tz":-420,"elapsed":333,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":1,"outputs":[]},{"cell_type":"code","source":["# Open the gzipped file\n","user_item_interactions = {}\n","data_dict = None\n","count = {\n","    \"users\": 0,\n","    \"items\": 0\n","}\n","data_items = None\n","with gzip.open(f\"{file_path}/{files[1]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            data_items = {}\n","            if data_dict[\"items_count\"] > 0:\n","              count[\"items\"] += data_dict[\"items_count\"]\n","              count[\"users\"] += 1\n","\n","              for item in data_dict[\"items\"]:\n","                data_items[item[\"item_id\"]] = item[\"playtime_forever\"]\n","\n","              user_item_interactions[data_dict['user_id']] = data_items\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","        if count[\"users\"] == 10000:\n","          break\n","\n","print(f\"Number of user {count['users']}\")\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yPu3n3l6hRLA","executionInfo":{"status":"ok","timestamp":1735799911615,"user_tz":-420,"elapsed":43404,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"6af90f51-dc97-42ad-a259-265c9a388a62"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of user 10000\n","Number of items 1132592\n","{'user_id': '76561198030000787', 'items_count': 314, 'steam_id': '76561198030000787', 'user_url': 'http://steamcommunity.com/profiles/76561198030000787', 'items': [{'item_id': '4000', 'item_name': \"Garry's Mod\", 'playtime_forever': 32, 'playtime_2weeks': 0}, {'item_id': '2600', 'item_name': 'Vampire: The Masquerade - Bloodlines', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '2200', 'item_name': 'Quake III Arena', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2310', 'item_name': 'Quake', 'playtime_forever': 26, 'playtime_2weeks': 0}, {'item_id': '2320', 'item_name': 'Quake II', 'playtime_forever': 5, 'playtime_2weeks': 0}, {'item_id': '2330', 'item_name': 'Quake II: The Reckoning', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2340', 'item_name': 'Quake II: Ground Zero', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '2350', 'item_name': 'Quake III: Team Arena', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9030', 'item_name': 'Quake Mission Pack 2: Dissolution of Eternity', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '9040', 'item_name': 'Quake Mission Pack 1: Scourge of Armagon', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '4760', 'item_name': 'Rome: Total War', 'playtime_forever': 124, 'playtime_2weeks': 0}, {'item_id': '4770', 'item_name': 'Rome: Total War - Alexander', 'playtime_forever': 5, 'playtime_2weeks': 0}, {'item_id': '18500', 'item_name': 'Defense Grid: The Awakening', 'playtime_forever': 486, 'playtime_2weeks': 0}, {'item_id': '17460', 'item_name': 'Mass Effect', 'playtime_forever': 1896, 'playtime_2weeks': 0}, {'item_id': '1250', 'item_name': 'Killing Floor', 'playtime_forever': 949, 'playtime_2weeks': 0}, {'item_id': '35420', 'item_name': 'Killing Floor Mod: Defence Alliance 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21680', 'item_name': 'Bionic Commando Rearmed', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21670', 'item_name': 'Bionic Commando', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '38400', 'item_name': 'Fallout', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '38410', 'item_name': 'Fallout 2', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '38420', 'item_name': 'Fallout Tactics', 'playtime_forever': 48, 'playtime_2weeks': 0}, {'item_id': '20900', 'item_name': 'The Witcher: Enhanced Edition', 'playtime_forever': 38, 'playtime_2weeks': 0}, {'item_id': '17450', 'item_name': 'Dragon Age: Origins', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '10180', 'item_name': 'Call of Duty: Modern Warfare 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '10190', 'item_name': 'Call of Duty: Modern Warfare 2 - Multiplayer', 'playtime_forever': 835, 'playtime_2weeks': 0}, {'item_id': '550', 'item_name': 'Left 4 Dead 2', 'playtime_forever': 683, 'playtime_2weeks': 0}, {'item_id': '223530', 'item_name': 'Left 4 Dead 2 Beta', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '22370', 'item_name': 'Fallout 3 - Game of the Year Edition', 'playtime_forever': 3, 'playtime_2weeks': 0}, {'item_id': '24980', 'item_name': 'Mass Effect 2', 'playtime_forever': 1837, 'playtime_2weeks': 0}, {'item_id': '33910', 'item_name': 'Arma 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '33930', 'item_name': 'Arma 2: Operation Arrowhead', 'playtime_forever': 57, 'playtime_2weeks': 0}, {'item_id': '219540', 'item_name': 'Arma 2: Operation Arrowhead Beta (Obsolete)', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '22380', 'item_name': 'Fallout: New Vegas', 'playtime_forever': 5078, 'playtime_2weeks': 0}, {'item_id': '42700', 'item_name': 'Call of Duty: Black Ops', 'playtime_forever': 537, 'playtime_2weeks': 0}, {'item_id': '42710', 'item_name': 'Call of Duty: Black Ops - Multiplayer', 'playtime_forever': 2037, 'playtime_2weeks': 0}, {'item_id': '47810', 'item_name': 'Dragon Age: Origins - Ultimate Edition', 'playtime_forever': 1522, 'playtime_2weeks': 0}, {'item_id': '78000', 'item_name': 'Bejeweled 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '56400', 'item_name': 'Warhammer® 40,000™: Dawn of War® II – Retribution™', 'playtime_forever': 917, 'playtime_2weeks': 0}, {'item_id': '48720', 'item_name': 'Mount & Blade: With Fire and Sword', 'playtime_forever': 424, 'playtime_2weeks': 0}, {'item_id': '20920', 'item_name': 'The Witcher 2: Assassins of Kings Enhanced Edition', 'playtime_forever': 2141, 'playtime_2weeks': 0}, {'item_id': '105600', 'item_name': 'Terraria', 'playtime_forever': 1807, 'playtime_2weeks': 0}, {'item_id': '17430', 'item_name': 'Need for Speed: Undercover', 'playtime_forever': 2, 'playtime_2weeks': 0}, {'item_id': '24740', 'item_name': 'Burnout Paradise: The Ultimate Box', 'playtime_forever': 48, 'playtime_2weeks': 0}, {'item_id': '24870', 'item_name': 'Need for Speed: SHIFT', 'playtime_forever': 102, 'playtime_2weeks': 0}, {'item_id': '47870', 'item_name': 'Need for Speed: Hot Pursuit', 'playtime_forever': 211, 'playtime_2weeks': 0}, {'item_id': '47920', 'item_name': 'Shift 2 Unleashed', 'playtime_forever': 7, 'playtime_2weeks': 0}, {'item_id': '33440', 'item_name': 'Driver San Francisco', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '72850', 'item_name': 'The Elder Scrolls V: Skyrim', 'playtime_forever': 10060, 'playtime_2weeks': 0}, {'item_id': '91310', 'item_name': 'Dead Island', 'playtime_forever': 1853, 'playtime_2weeks': 0}, {'item_id': '111400', 'item_name': 'Bunch Of Heroes', 'playtime_forever': 167, 'playtime_2weeks': 0}, {'item_id': '45770', 'item_name': 'Dead Rising 2: Off the Record', 'playtime_forever': 206, 'playtime_2weeks': 0}, {'item_id': '102600', 'item_name': 'Orcs Must Die!', 'playtime_forever': 209, 'playtime_2weeks': 0}, {'item_id': '48220', 'item_name': 'Might & Magic: Heroes VI', 'playtime_forever': 1314, 'playtime_2weeks': 0}, {'item_id': '110800', 'item_name': 'L.A. Noire', 'playtime_forever': 243, 'playtime_2weeks': 0}, {'item_id': '16450', 'item_name': 'F.E.A.R. 2: Project Origin', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21000', 'item_name': 'LEGO Batman: The Videogame', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21010', 'item_name': 'Watchmen: The End Is Nigh', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21030', 'item_name': 'Watchmen: The End Is Nigh Part 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21070', 'item_name': 'Wanted: Weapons of Fate', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21080', 'item_name': 'Terminator Salvation', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21090', 'item_name': 'F.E.A.R.', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21100', 'item_name': 'F.E.A.R. 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21110', 'item_name': 'F.E.A.R.: Extraction Point', 'playtime_forever': 4, 'playtime_2weeks': 0}, {'item_id': '21120', 'item_name': 'F.E.A.R.: Perseus Mandate', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '21130', 'item_name': 'Lego Harry Potter', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32800', 'item_name': 'The Lord of the Rings: War in the North', 'playtime_forever': 64, 'playtime_2weeks': 0}, {'item_id': '35140', 'item_name': 'Batman: Arkham Asylum GOTY Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '57400', 'item_name': 'Batman: Arkham City™', 'playtime_forever': 1924, 'playtime_2weeks': 0}, {'item_id': '107100', 'item_name': 'Bastion', 'playtime_forever': 36, 'playtime_2weeks': 0}, {'item_id': '200260', 'item_name': 'Batman: Arkham City GOTY', 'playtime_forever': 18, 'playtime_2weeks': 0}, {'item_id': '205790', 'item_name': 'Dota 2 Test', 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '3900', 'item_name': \"Sid Meier's Civilization IV\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '3910', 'item_name': \"Sid Meier's Civilization III: Complete\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '3920', 'item_name': \"Sid Meier's Pirates!\", 'playtime_forever': 91, 'playtime_2weeks': 0}, {'item_id': '3990', 'item_name': \"Sid Meier's Civilization IV: Warlords\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7650', 'item_name': 'X-COM: Terror from the Deep', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7660', 'item_name': 'X-COM: Apocalypse', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7670', 'item_name': 'BioShock', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7730', 'item_name': 'X-COM: Interceptor', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '7760', 'item_name': 'X-COM: UFO Defense', 'playtime_forever': 27, 'playtime_2weeks': 0}, {'item_id': '7770', 'item_name': 'X-COM: Enforcer', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8800', 'item_name': \"Sid Meier's Civilization IV: Beyond the Sword\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8850', 'item_name': 'BioShock 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8880', 'item_name': 'Freedom Force', 'playtime_forever': 98, 'playtime_2weeks': 0}, {'item_id': '8890', 'item_name': 'Freedom Force vs. the 3rd Reich', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8930', 'item_name': \"Sid Meier's Civilization V\", 'playtime_forever': 1591, 'playtime_2weeks': 0}, {'item_id': '8970', 'item_name': 'Axel & Pixel', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8980', 'item_name': 'Borderlands', 'playtime_forever': 12, 'playtime_2weeks': 0}, {'item_id': '16810', 'item_name': \"Sid Meier's Civilization IV: Colonization\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34440', 'item_name': \"Sid Meier's Civilization IV\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34450', 'item_name': \"Sid Meier's Civilization IV: Warlords\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '34460', 'item_name': \"Sid Meier's Civilization IV: Beyond the Sword\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40920', 'item_name': 'NBA 2K10', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40930', 'item_name': 'The Misadventures of P.B. Winterbottom', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '40990', 'item_name': 'Mafia', 'playtime_forever': 21, 'playtime_2weeks': 0}, {'item_id': '50130', 'item_name': 'Mafia II', 'playtime_forever': 300, 'playtime_2weeks': 0}, {'item_id': '50310', 'item_name': 'MLB 2K11', 'playtime_forever': 9, 'playtime_2weeks': 0}, {'item_id': '57900', 'item_name': 'Duke Nukem Forever', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '65950', 'item_name': 'NBA 2K11', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '201020', 'item_name': 'NBA 2K12', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '409710', 'item_name': 'BioShock Remastered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '409720', 'item_name': 'BioShock 2 Remastered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '67370', 'item_name': 'The Darkness II', 'playtime_forever': 146, 'playtime_2weeks': 0}, {'item_id': '207610', 'item_name': 'The Walking Dead', 'playtime_forever': 457, 'playtime_2weeks': 0}, {'item_id': '97330', 'item_name': 'Magic: The Gathering - Duels of the Planeswalkers 2013', 'playtime_forever': 300, 'playtime_2weeks': 0}, {'item_id': '65800', 'item_name': 'Dungeon Defenders', 'playtime_forever': 4376, 'playtime_2weeks': 0}, {'item_id': '211420', 'item_name': 'Dark Souls: Prepare to Die Edition', 'playtime_forever': 71, 'playtime_2weeks': 0}, {'item_id': '730', 'item_name': 'Counter-Strike: Global Offensive', 'playtime_forever': 1900, 'playtime_2weeks': 0}, {'item_id': '204300', 'item_name': 'Awesomenauts', 'playtime_forever': 584, 'playtime_2weeks': 0}, {'item_id': '200170', 'item_name': 'Worms Revolution', 'playtime_forever': 423, 'playtime_2weeks': 0}, {'item_id': '217200', 'item_name': 'Worms Armageddon', 'playtime_forever': 4, 'playtime_2weeks': 0}, {'item_id': '204360', 'item_name': 'Castle Crashers', 'playtime_forever': 614, 'playtime_2weeks': 0}, {'item_id': '49520', 'item_name': 'Borderlands 2', 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'item_name': 'Loadout', 'playtime_forever': 140, 'playtime_2weeks': 0}, {'item_id': '212500', 'item_name': 'The Lord of the Rings Online™', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '218230', 'item_name': 'PlanetSide 2', 'playtime_forever': 2808, 'playtime_2weeks': 0}, {'item_id': '230410', 'item_name': 'Warframe', 'playtime_forever': 252, 'playtime_2weeks': 0}, {'item_id': '236390', 'item_name': 'War Thunder', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '238960', 'item_name': 'Path of Exile', 'playtime_forever': 3579, 'playtime_2weeks': 0}, {'item_id': '243870', 'item_name': \"Tom Clancy's Ghost Recon Phantoms - NA\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '263500', 'item_name': 'Dragons and Titans', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '39120', 'item_name': 'RIFT', 'playtime_forever': 2866, 'playtime_2weeks': 0}, {'item_id': '242720', 'item_name': 'GunZ 2: The Second Duel', 'playtime_forever': 0, 'playtime_2weeks': 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'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32370', 'item_name': 'STAR WARS™: Knights of the Old Republic™', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32380', 'item_name': 'STAR WARS™ Jedi Knight: Dark Forces II', 'playtime_forever': 3, 'playtime_2weeks': 0}, {'item_id': '32390', 'item_name': 'STAR WARS™ Jedi Knight: Mysteries of the Sith™', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32400', 'item_name': 'STAR WARS™: Dark Forces', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32420', 'item_name': 'STAR WARS™: The Clone Wars - Republic Heroes™', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32430', 'item_name': 'STAR WARS™: The Force Unleashed™ Ultimate Sith Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32470', 'item_name': 'STAR WARS™ Empire at War: Gold Pack', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '32500', 'item_name': 'STAR WARS™: The Force Unleashed™ II', 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'playtime_2weeks': 0}, {'item_id': '242760', 'item_name': 'The Forest', 'playtime_forever': 1677, 'playtime_2weeks': 0}, {'item_id': '206420', 'item_name': 'Saints Row IV', 'playtime_forever': 2402, 'playtime_2weeks': 0}, {'item_id': '213850', 'item_name': 'Magic 2014 ', 'playtime_forever': 861, 'playtime_2weeks': 0}, {'item_id': '244810', 'item_name': 'Foul Play', 'playtime_forever': 19, 'playtime_2weeks': 0}, {'item_id': '244850', 'item_name': 'Space Engineers', 'playtime_forever': 60, 'playtime_2weeks': 0}, {'item_id': '6880', 'item_name': 'Just Cause', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '8190', 'item_name': 'Just Cause 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '239030', 'item_name': 'Papers, Please', 'playtime_forever': 98, 'playtime_2weeks': 0}, {'item_id': '218620', 'item_name': 'PAYDAY 2', 'playtime_forever': 2741, 'playtime_2weeks': 0}, {'item_id': '209000', 'item_name': 'Batman™: Arkham Origins', 'playtime_forever': 2369, 'playtime_2weeks': 0}, {'item_id': '239820', 'item_name': 'Game Dev Tycoon', 'playtime_forever': 448, 'playtime_2weeks': 0}, {'item_id': '250320', 'item_name': 'The Wolf Among Us', 'playtime_forever': 668, 'playtime_2weeks': 0}, {'item_id': '219640', 'item_name': 'Chivalry: Medieval Warfare', 'playtime_forever': 34, 'playtime_2weeks': 0}, {'item_id': '232210', 'item_name': 'Patch testing for Chivalry', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '208610', 'item_name': 'Skullgirls ∞Endless Beta∞', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '245170', 'item_name': 'Skullgirls', 'playtime_forever': 212, 'playtime_2weeks': 0}, {'item_id': '228560', 'item_name': 'Teenage Mutant Ninja Turtles: Out of the Shadows', 'playtime_forever': 1237, 'playtime_2weeks': 0}, {'item_id': '251570', 'item_name': '7 Days to Die', 'playtime_forever': 3034, 'playtime_2weeks': 0}, {'item_id': '252350', 'item_name': 'Double Dragon Neon', 'playtime_forever': 264, 'playtime_2weeks': 0}, {'item_id': '252490', 'item_name': 'Rust', 'playtime_forever': 3483, 'playtime_2weeks': 0}, {'item_id': '252950', 'item_name': 'Rocket League', 'playtime_forever': 915, 'playtime_2weeks': 0}, {'item_id': '241540', 'item_name': 'State of Decay', 'playtime_forever': 2099, 'playtime_2weeks': 0}, {'item_id': '237890', 'item_name': 'Agarest: Generations of War', 'playtime_forever': 135, 'playtime_2weeks': 0}, {'item_id': '242050', 'item_name': \"Assassin's Creed IV Black Flag\", 'playtime_forever': 6221, 'playtime_2weeks': 0}, {'item_id': '234530', 'item_name': 'War of the Vikings', 'playtime_forever': 2509, 'playtime_2weeks': 0}, {'item_id': '257350', 'item_name': \"Baldur's Gate II: Enhanced Edition\", 'playtime_forever': 1, 'playtime_2weeks': 0}, {'item_id': '243470', 'item_name': 'Watch_Dogs', 'playtime_forever': 2043, 'playtime_2weeks': 0}, {'item_id': '247730', 'item_name': 'Nether', 'playtime_forever': 3114, 'playtime_2weeks': 0}, {'item_id': '260730', 'item_name': 'Desperados - Wanted Dead or Alive', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '261030', 'item_name': 'The Walking Dead: Season Two', 'playtime_forever': 637, 'playtime_2weeks': 0}, {'item_id': '242700', 'item_name': 'Injustice: Gods Among Us Ultimate Edition', 'playtime_forever': 368, 'playtime_2weeks': 0}, {'item_id': '262060', 'item_name': 'Darkest Dungeon', 'playtime_forever': 332, 'playtime_2weeks': 0}, {'item_id': '263440', 'item_name': 'The Stomping Land', 'playtime_forever': 142, 'playtime_2weeks': 0}, {'item_id': '108600', 'item_name': 'Project Zomboid', 'playtime_forever': 160, 'playtime_2weeks': 0}, {'item_id': '211820', 'item_name': 'Starbound', 'playtime_forever': 137, 'playtime_2weeks': 0}, {'item_id': '367540', 'item_name': 'Starbound - Unstable', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '41900', 'item_name': \"The Bard's Tale\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '240760', 'item_name': 'Wasteland 2', 'playtime_forever': 710, 'playtime_2weeks': 0}, {'item_id': '259130', 'item_name': 'Wasteland 1 - The Original Classic', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '404730', 'item_name': \"Wasteland 2: Director's Cut\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '221100', 'item_name': 'DayZ', 'playtime_forever': 131, 'playtime_2weeks': 0}, {'item_id': '202170', 'item_name': 'Sleeping Dogs™', 'playtime_forever': 1322, 'playtime_2weeks': 0}, {'item_id': '268870', 'item_name': 'Satellite Reign', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '239840', 'item_name': 'Dead State', 'playtime_forever': 718, 'playtime_2weeks': 0}, {'item_id': '271590', 'item_name': 'Grand Theft Auto V', 'playtime_forever': 6740, 'playtime_2weeks': 0}, {'item_id': '273110', 'item_name': 'Counter-Strike Nexon: Zombies', 'playtime_forever': 6, 'playtime_2weeks': 0}, {'item_id': '274310', 'item_name': 'Always Sometimes Monsters', 'playtime_forever': 501, 'playtime_2weeks': 0}, {'item_id': '213670', 'item_name': 'South Park™: The Stick of Truth™', 'playtime_forever': 1105, 'playtime_2weeks': 0}, {'item_id': '278080', 'item_name': 'DYNASTY WARRIORS 8: Xtreme Legends Complete Edition', 'playtime_forever': 671, 'playtime_2weeks': 0}, {'item_id': '48700', 'item_name': 'Mount & Blade: Warband', 'playtime_forever': 871, 'playtime_2weeks': 0}, {'item_id': '254700', 'item_name': 'resident evil 4 / biohazard 4', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '235210', 'item_name': 'Strider', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '290140', 'item_name': 'Echo of Soul', 'playtime_forever': 44, 'playtime_2weeks': 0}, {'item_id': '290300', 'item_name': 'Rebel Galaxy', 'playtime_forever': 96, 'playtime_2weeks': 0}, {'item_id': '293780', 'item_name': 'Crawl', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '295110', 'item_name': 'H1Z1: Just Survive', 'playtime_forever': 4778, 'playtime_2weeks': 0}, {'item_id': '362300', 'item_name': 'H1Z1: Just Survive Test Server', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '433850', 'item_name': 'H1Z1: King of the Kill', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '439700', 'item_name': 'H1Z1: King of the Kill Test Server', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '222900', 'item_name': 'Dead Island: Epidemic', 'playtime_forever': 268, 'playtime_2weeks': 0}, {'item_id': '300550', 'item_name': \"Shadowrun: Dragonfall - Director's Cut\", 'playtime_forever': 1056, 'playtime_2weeks': 0}, {'item_id': '300570', 'item_name': 'Infinifactory', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '300580', 'item_name': 'GALAK-Z', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '301520', 'item_name': 'Robocraft', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '302270', 'item_name': 'Dungeon Defenders Eternity', 'playtime_forever': 551, 'playtime_2weeks': 0}, {'item_id': '304050', 'item_name': 'Trove', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '304030', 'item_name': 'ArcheAge', 'playtime_forever': 12249, 'playtime_2weeks': 0}, {'item_id': '304930', 'item_name': 'Unturned', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '244630', 'item_name': 'NEOTOKYO°', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '312990', 'item_name': 'The Expendabros', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '227940', 'item_name': 'Heroes & Generals', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '265590', 'item_name': 'The Red Solstice', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '241930', 'item_name': 'Middle-earth: Shadow of Mordor', 'playtime_forever': 1494, 'playtime_2weeks': 0}, {'item_id': '265550', 'item_name': 'Dead Rising 3', 'playtime_forever': 171, 'playtime_2weeks': 0}, {'item_id': '226720', 'item_name': 'Lost Planet 3', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '323370', 'item_name': 'TERA', 'playtime_forever': 1785, 'playtime_2weeks': 0}, {'item_id': '327510', 'item_name': 'WASTED', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '261640', 'item_name': 'Borderlands: The Pre-Sequel', 'playtime_forever': 2462, 'playtime_2weeks': 0}, {'item_id': '330840', 'item_name': 'Game of Thrones - A Telltale Games Series', 'playtime_forever': 719, 'playtime_2weeks': 0}, {'item_id': '17570', 'item_name': 'Pirates, Vikings, & Knights II', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '305620', 'item_name': 'The Long Dark', 'playtime_forever': 404, 'playtime_2weeks': 0}, {'item_id': '323470', 'item_name': 'DRAGON BALL XENOVERSE', 'playtime_forever': 920, 'playtime_2weeks': 0}, {'item_id': '333930', 'item_name': 'Dirty Bomb', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '249050', 'item_name': 'Dungeon of the Endless', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '236110', 'item_name': 'Dungeon Defenders II', 'playtime_forever': 88, 'playtime_2weeks': 0}, {'item_id': '337850', 'item_name': 'Avernum 2: Crystal Souls', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '339120', 'item_name': \"Fork Parker's Holiday Profit Hike\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '342200', 'item_name': 'MechWarrior Online', 'playtime_forever': 699, 'playtime_2weeks': 0}, {'item_id': '314660', 'item_name': \"Oddworld: New 'n' Tasty\", 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '345520', 'item_name': 'Infinite Crisis™', 'playtime_forever': 406, 'playtime_2weeks': 0}, {'item_id': '346110', 'item_name': 'ARK: Survival Evolved', 'playtime_forever': 23434, 'playtime_2weeks': 0}, {'item_id': '407530', 'item_name': 'ARK: Survival Of The Fittest', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '347160', 'item_name': 'Steredenn', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '287290', 'item_name': 'Resident Evil Revelations 2 / Biohazard Revelations 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '339280', 'item_name': 'Strife', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '351570', 'item_name': 'Killing Floor: Uncovered', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '232090', 'item_name': 'Killing Floor 2', 'playtime_forever': 1171, 'playtime_2weeks': 0}, {'item_id': '232150', 'item_name': 'Killing Floor 2 - SDK', 'playtime_forever': 2, 'playtime_2weeks': 0}, {'item_id': '362070', 'item_name': 'Metal Reaper Online', 'playtime_forever': 8, 'playtime_2weeks': 0}, {'item_id': '47780', 'item_name': 'Dead Space 2', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '362680', 'item_name': 'Fran Bow', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '329460', 'item_name': 'JumpJet Rex', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '365590', 'item_name': \"Tom Clancy's The Division\", 'playtime_forever': 10442, 'playtime_2weeks': 0}, {'item_id': '329050', 'item_name': 'Devil May Cry® 4 Special Edition', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '370360', 'item_name': 'TIS-100', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '292030', 'item_name': 'The Witcher 3: Wild Hunt', 'playtime_forever': 2140, 'playtime_2weeks': 0}, {'item_id': '373480', 'item_name': '1993 Space Machine', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '377160', 'item_name': 'Fallout 4', 'playtime_forever': 7194, 'playtime_2weeks': 0}, {'item_id': '386070', 'item_name': 'Planetary Annihilation: TITANS', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '386360', 'item_name': 'SMITE', 'playtime_forever': 498, 'playtime_2weeks': 0}, {'item_id': '234140', 'item_name': 'Mad Max', 'playtime_forever': 1123, 'playtime_2weeks': 0}, {'item_id': '393420', 'item_name': 'Hurtworld', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '445900', 'item_name': 'Hurtworld SDK', 'playtime_forever': 0, 'playtime_2weeks': 0}, {'item_id': '394310', 'item_name': 'Punch Club', 'playtime_forever': 416, 'playtime_2weeks': 0}, {'item_id': '413150', 'item_name': 'Stardew Valley', 'playtime_forever': 1321, 'playtime_2weeks': 0}, {'item_id': '268500', 'item_name': 'XCOM 2', 'playtime_forever': 620, 'playtime_2weeks': 0}, {'item_id': '444560', 'item_name': 'Agent Origins: Escape', 'playtime_forever': 9, 'playtime_2weeks': 0}, {'item_id': '275850', 'item_name': \"No Man's Sky\", 'playtime_forever': 564, 'playtime_2weeks': 0}]}\n"]}]},{"cell_type":"code","source":["# Open the gzipped file\n","bundle_data = {}\n","data_dict = None\n","count = {\n","    \"bundles\": 0,\n","    \"items\": 0\n","}\n","data_items = None\n","with gzip.open(f\"{file_path}/{files[2]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            data_items = set()\n","\n","            if len(data_dict[\"items\"]) > 0:\n","              count[\"items\"] += len(data_dict[\"items\"])\n","              count[\"bundles\"] += 1\n","\n","              for item in data_dict[\"items\"]:\n","                data_items.add(item[\"item_id\"])\n","\n","              bundle_data[data_dict['bundle_id']] = data_items\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","print(f\"Number of bundle {count['bundles']}\")\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ZnLJTSvOm6tH","executionInfo":{"status":"ok","timestamp":1735799912095,"user_tz":-420,"elapsed":482,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"7f9aad26-4af2-4f9e-d5b6-3925ce3d9dbb"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of bundle 615\n","Number of items 3525\n","{'bundle_final_price': '$4.77', 'bundle_url': 'http://store.steampowered.com/bundle/594/?utm_source=SteamDB&utm_medium=SteamDB&utm_campaign=SteamDB%20Bundles%20Page', 'bundle_price': '$5.97', 'bundle_name': 'The Ninjahtic Series', 'bundle_id': '594', 'items': [{'genre': 'Action, Adventure, Indie', 'item_id': '385230', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/385230', 'item_name': 'Ninjahtic'}, {'genre': 'Action, Adventure, Indie', 'item_id': '387880', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/387880', 'item_name': 'Ninjahtic Mind Tricks'}, {'genre': 'Action, Indie', 'item_id': '454130', 'discounted_price': '$1.99', 'item_url': 'http://store.steampowered.com/app/454130', 'item_name': 'Nil-Ninjahtic: Ronin'}], 'bundle_discount': '20%'}\n"]}]},{"cell_type":"code","source":["# Open the gzipped file\n","items_dictionary = {}\n","data_dict = None\n","count = {\n","    \"items\": 0\n","}\n","with gzip.open(f\"{file_path}/{files[3]}\", 'rt', encoding='utf-8') as f:  # 'rt' is for text mode\n","    for i, line in enumerate(f):\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","            if 'id' in data_dict:\n","              items_dictionary[data_dict['id']] = data_dict\n","              count[\"items\"] += 1\n","        except (ValueError, SyntaxError) as e:\n","            print(f\"Failed to convert string to dictionary: {e}\")\n","\n","print(f\"Number of items {count['items']}\")\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KwK2r2ospM7p","executionInfo":{"status":"ok","timestamp":1735799916743,"user_tz":-420,"elapsed":4650,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"c7a1870a-7b0e-44e9-d7be-4af1daa44ba1"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Number of items 32133\n","{'app_name': 'Maze Run VR', 'sentiment': 'Positive', 'tags': ['Early Access', 'Adventure', 'Indie', 'Action', 'Simulation', 'VR'], 'url': 'http://store.steampowered.com/app/681550/Maze_Run_VR/', 'price': 4.99, 'reviews_url': 'http://steamcommunity.com/app/681550/reviews/?browsefilter=mostrecent&p=1', 'id': '681550', 'early_access': True, 'specs': ['Single-player', 'Stats', 'Steam Leaderboards', 'HTC Vive', 'Oculus Rift', 'Tracked Motion Controllers', 'Standing', 'Room-Scale']}\n"]}]},{"cell_type":"code","source":["# prompt: Show me distribution of sentiment attribute on items_dictionary\n","\n","import matplotlib.pyplot as plt\n","\n","# Assuming 'items_dictionary' is defined and accessible\n","\n","sentiment_counts = {}\n","for item_id, item_data in items_dictionary.items():\n","    if 'sentiment' in item_data:\n","        sentiment = item_data['sentiment']\n","        sentiment_counts[sentiment] = sentiment_counts.get(sentiment, 0) + 1\n","\n","sentiments, counts = zip(*sentiment_counts.items())\n","\n","plt.figure(figsize=(10, 6))\n","plt.bar(sentiments, counts, color='skyblue')\n","plt.xlabel(\"Sentiment\")\n","plt.ylabel(\"Number of Items\")\n","plt.title(\"Distribution of Sentiment Attribute in items_dictionary\")\n","plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for better readability\n","plt.tight_layout() # Adjust layout to prevent labels from overlapping\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":607},"id":"9HG4u_54plVH","executionInfo":{"status":"ok","timestamp":1735479680885,"user_tz":-420,"elapsed":730,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"2a732e27-e0bc-41f3-8417-703fc4de328b"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["# prompt: From data sentiment_counts i want to sorted from very positive to very negative\n","\n","import operator\n","\n","sorted_sentiment_counts = dict(sorted(sentiment_counts.items(), key=operator.itemgetter(1), reverse=True))\n","\n","sentiments, counts = zip(*sorted_sentiment_counts.items())\n","\n","plt.figure(figsize=(10, 6))\n","plt.bar(sentiments, counts, color='skyblue')\n","plt.xlabel(\"Sentiment\")\n","plt.ylabel(\"Number of Items\")\n","plt.title(\"Distribution of Sentiment Attribute in items_dictionary (Sorted)\")\n","plt.xticks(rotation=45, ha='right')  # Rotate x-axis labels for better readability\n","plt.tight_layout() # Adjust layout to prevent labels from overlapping\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":607},"id":"sjR-gufgppmg","executionInfo":{"status":"ok","timestamp":1735479926795,"user_tz":-420,"elapsed":948,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"e8acb122-9e3e-4b2d-fd64-15bfc992059f"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["def generate_sentiment_value(sentimen_str):\n","  if sentimen_str == 'Overwhelmingly Positive':\n","    return 1.00\n","  elif sentimen_str == 'Very Positive':\n","    return 0.80\n","  elif sentimen_str == 'Positive':\n","    return 0.60\n","  elif sentimen_str == 'Mostly Positive':\n","    return 0.40\n","  elif sentimen_str == '9 user reviews':\n","    return 0.25\n","  elif sentimen_str == '8 user reviews':\n","    return 0.20\n","  elif sentimen_str == '7 user reviews':\n","    return 0.15\n","  elif sentimen_str == '6 user reviews':\n","    return 0.10\n","  elif sentimen_str == 'Mixed':\n","    return 0.5\n","  elif sentimen_str == '5 user reviews':\n","    return -0.5\n","  elif sentimen_str == '4 user reviews':\n","    return -0.10\n","  elif sentimen_str == '3 user reviews':\n","    return -0.15\n","  elif sentimen_str == '2 user reviews':\n","    return -0.20\n","  elif sentimen_str == '1 user review':\n","    return -0.25\n","  elif sentimen_str == 'Mostly Negative':\n","    return -0.40\n","  elif sentimen_str == 'Negative':\n","    return -0.60\n","  elif sentimen_str == 'Very Negative':\n","    return -0.85\n","  elif sentimen_str == 'Overwhelmingly Negative':\n","    return -1.00\n","  else:\n","    return 0.00"],"metadata":{"id":"Pd-DAKhQtwcR","executionInfo":{"status":"ok","timestamp":1735799166536,"user_tz":-420,"elapsed":3,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":5,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"n1KqBF9ifNWl","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1735482868636,"user_tz":-420,"elapsed":162397,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"f8d4b6ff-d602-481e-ebdc-3762bd5dda2c"},"outputs":[{"output_type":"stream","name":"stdout","text":["{'user_id': '76561198030000787', 'bundle_id': '1183', 'is_recommended': '0'}\n"]}],"source":["import pandas as pd\n","import json\n","import gzip\n","import operator\n","\n","filepath_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs/recommendation_data_knn.json.gz'\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_knn.json.gz'\n","\n","data_dict = None\n","\n","users_ids = set()\n","users_bundle_candidate_bfr = set()\n","users_bundle_candidate_bfr_sentiment = {}\n","\n","with gzip.open(filepath_rec_data, 'rt', encoding='utf-8') as file, gzip.open(filepath_rarank_rec_data, 'wt', encoding='utf-8') as outfile:\n","    for line in file:\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","\n","            if int(data_dict[\"is_recommended\"]) == 1:\n","              users_bundle_candidate_bfr.add(data_dict['bundle_id'])\n","\n","            if data_dict['user_id'] not in users_ids:\n","              # Handle for the first checkking\n","              if len(users_ids) == 0:\n","                users_ids.add(data_dict['user_id'])\n","              else:\n","                # Do Reranking here\n","                for bundle_id in users_bundle_candidate_bfr:\n","                  users_bundle_candidate_bfr_sentiment[bundle_id] = 0\n","                  for item_id in bundle_data[bundle_id]:\n","                    if item_id in items_dictionary and \"sentiment\" in items_dictionary[item_id]:\n","                      users_bundle_candidate_bfr_sentiment[bundle_id] += generate_sentiment_value(items_dictionary[item_id]['sentiment'])\n","\n","                users_bundle_candidate_bfr = sorted(users_bundle_candidate_bfr_sentiment.items(), key=operator.itemgetter(1), reverse=True)\n","\n","                json.dump({ \"user_id\": data_dict['user_id'], \"rec_bundles\": dict(users_bundle_candidate_bfr) }, outfile, ensure_ascii=False)\n","                outfile.write('\\n')\n","\n","                # Reset data\n","                users_ids.add(data_dict['user_id'])\n","                users_bundle_candidate_bfr = set()\n","                users_bundle_candidate_bfr_sentiment = {}\n","        except json.JSONDecodeError as e:\n","            print(f\"Error decoding JSON line: {e}\")\n","            # Handle the error as needed (e.g., skip the line, log the error, etc.)\n","\n","print(data_dict)"]},{"cell_type":"code","source":["import pandas as pd\n","import json\n","import gzip\n","import operator\n","\n","filepath_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns/recommendation_data_knn.json.gz'\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_knn.json.gz'\n","\n","data_dict = None\n","\n","users_ids = set()\n","users_bundle_candidate_bfr = set()\n","users_bundle_candidate_bfr_sentiment = {}\n","\n","with gzip.open(filepath_rec_data, 'rt', encoding='utf-8') as file, gzip.open(filepath_rarank_rec_data, 'wt', encoding='utf-8') as outfile:\n","    for line in file:\n","        # Remove the trailing newline character\n","        cleaned_string = line.strip()\n","        try:\n","            data_dict = ast.literal_eval(cleaned_string)\n","\n","            if int(data_dict[\"is_recommended\"]) == 1:\n","              users_bundle_candidate_bfr.add(data_dict['bundle_id'])\n","\n","            if data_dict['user_id'] not in users_ids:\n","              # Handle for the first checkking\n","              if len(users_ids) == 0:\n","                users_ids.add(data_dict['user_id'])\n","              else:\n","                # Do Reranking here\n","                for bundle_id in users_bundle_candidate_bfr:\n","                  users_bundle_candidate_bfr_sentiment[bundle_id] = 0\n","                  for item_id in bundle_data[bundle_id]:\n","                    if item_id in items_dictionary and \"sentiment\" in items_dictionary[item_id]:\n","                      users_bundle_candidate_bfr_sentiment[bundle_id] += generate_sentiment_value(items_dictionary[item_id]['sentiment'])\n","\n","                users_bundle_candidate_bfr = sorted(users_bundle_candidate_bfr_sentiment.items(), key=operator.itemgetter(1), reverse=True)\n","\n","                json.dump({ \"user_id\": data_dict['user_id'], \"rec_bundles\": dict(users_bundle_candidate_bfr) }, outfile, ensure_ascii=False)\n","                outfile.write('\\n')\n","\n","                # Reset data\n","                users_ids.add(data_dict['user_id'])\n","                users_bundle_candidate_bfr = set()\n","                users_bundle_candidate_bfr_sentiment = {}\n","        except json.JSONDecodeError as e:\n","            print(f\"Error decoding JSON line: {e}\")\n","            # Handle the error as needed (e.g., skip the line, log the error, etc.)\n","\n","print(data_dict)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sYOVjEBOpk9b","executionInfo":{"status":"ok","timestamp":1735799315858,"user_tz":-420,"elapsed":149324,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"63cca272-2476-400e-c203-6ec8a43e52ba"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["{'user_id': '76561198030000787', 'bundle_id': '594', 'is_recommended': '0'}\n"]}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","\n","count = 0\n","countall = 0\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","                if len(data_dict['rec_bundles']) > 0:\n","                  count += 1\n","                countall += 1\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count} / {countall}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-nz3SqNvj-F7","executionInfo":{"status":"ok","timestamp":1735799452872,"user_tz":-420,"elapsed":614,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"df52527c-6371-47ec-d6d9-e14a4afa3fbb"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["File '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_knn.json.gz' successfully processed and saved to '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_knn.json.gz'\n","Count: 5075 / 9875\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"FKMJ7w60S-QM"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Evaluate\n"],"metadata":{"id":"q1DFXWFOCsP0"}},{"cell_type":"code","source":["# prompt: get top rec_bundles from data_dict with variation TOP 5 until top 20 with space 5\n","\n","def get_top_rec_bundles(data_dict, start=5, end=20, step=5):\n","  \"\"\"\n","  Gets top recommended bundles from data_dict with variations.\n","\n","  Args:\n","    data_dict: A dictionary containing recommendation data.\n","    start: The starting rank of top bundles.\n","    end: The ending rank of top bundles.\n","    step: The increment in rank.\n","\n","  Returns:\n","    A list of dictionaries, where each dictionary contains the user ID and top recommended bundles for a specified range.\n","    Returns an empty list if 'rec_bundles' key not found in data_dict.\n","  \"\"\"\n","\n","  if 'rec_bundles' not in data_dict:\n","    return []\n","\n","  results = []\n","  for top_n in range(start, end + 1, step):\n","    top_bundles = dict(sorted(data_dict['rec_bundles'].items(), key=lambda item: item[1], reverse=True)[:top_n])\n","    results.append({\"user_id\": data_dict['user_id'], \"top_rec_bundles\": top_bundles, \"top_n\": top_n})\n","  return results\n","\n","# Example usage (assuming data_dict is defined as in the provided code)\n","# Assuming data_dict contains the following:\n","# data_dict = {\"user_id\": 123, \"rec_bundles\": {\"bundle_1\": 0.9, \"bundle_2\": 0.8, \"bundle_3\": 0.7, \"bundle_4\": 0.6, \"bundle_5\": 0.5, \"bundle_6\": 0.4, \"bundle_7\": 0.3, \"bundle_8\":0.2, \"bundle_9\":0.1, \"bundle_10\": 0.0}}"],"metadata":{"id":"1M0JQWwPEAK5","executionInfo":{"status":"ok","timestamp":1735799916743,"user_tz":-420,"elapsed":4,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":5,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate hit_ratio from top_bundles_results by calculating how many items from user_item_interactions is on bundle_data by bundle_id and item_id\n","\n","def calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data):\n","    \"\"\"\n","    Calculates the hit ratio based on the provided data.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        user_item_interactions: A dictionary mapping user IDs to their item interactions.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and hit ratio.\n","    \"\"\"\n","\n","    hit_ratios = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        hits = 0\n","        if user_id in user_item_interactions:\n","            user_items = set(user_item_interactions[user_id].keys())\n","            for bundle_id in top_bundles:\n","                if bundle_id in bundle_data:\n","                  bundle_items = bundle_data[bundle_id]\n","                  hits += len(user_items.intersection(bundle_items))\n","\n","        hit_ratio = hits / top_n if top_n > 0 else 0  # Avoid division by zero\n","        hit_ratios.append({\"user_id\": user_id, \"top_n\": top_n, \"hit_ratio\": hit_ratio})\n","    return hit_ratios"],"metadata":{"id":"OBktUkbTEm5u","executionInfo":{"status":"ok","timestamp":1735799916743,"user_tz":-420,"elapsed":3,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate diversity from top_bundles_results by calculating how many items from user_item_interactions is on bundle_data by bundle_id and item_id\n","\n","def calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data):\n","    \"\"\"\n","    Calculates the diversity of recommended bundles.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        user_item_interactions: A dictionary mapping user IDs to their item interactions.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and diversity score.\n","    \"\"\"\n","    diversity_scores = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        total_items = 0\n","        unique_items = set()\n","\n","        for bundle_id in top_bundles:\n","          if bundle_id in bundle_data:\n","            bundle_items = bundle_data[bundle_id]\n","            total_items += len(bundle_items)\n","            unique_items.update(bundle_items)\n","\n","        diversity = len(unique_items) / total_items if total_items > 0 else 0\n","        diversity_scores.append({\"user_id\": user_id, \"top_n\": top_n, \"diversity\": diversity})\n","    return diversity_scores"],"metadata":{"id":"Y9x5v5iNFzlZ","executionInfo":{"status":"ok","timestamp":1735799916744,"user_tz":-420,"elapsed":4,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["# prompt: Calculate inter_diversity from top_bundles_results by checkking how similar for each bundle\n","\n","import json\n","import gzip\n","import ast\n","import matplotlib.pyplot as plt\n","import operator\n","import pandas as pd\n","\n","# ... (Your existing code)\n","\n","def calculate_inter_diversity(top_bundles_results, bundle_data):\n","    \"\"\"\n","    Calculates the inter-diversity of recommended bundles.\n","\n","    Args:\n","        top_bundles_results: A list of dictionaries, where each dictionary contains user ID and top recommended bundles.\n","        bundle_data: A dictionary mapping bundle IDs to their items.\n","\n","    Returns:\n","        A list of dictionaries, each containing the user ID, top N, and inter-diversity score.\n","    \"\"\"\n","    inter_diversity_scores = []\n","    for result in top_bundles_results:\n","        user_id = result['user_id']\n","        top_n = result['top_n']\n","        top_bundles = result['top_rec_bundles']\n","\n","        jaccard_similarities = []\n","        bundle_ids = list(top_bundles.keys())\n","        for i in range(len(bundle_ids)):\n","            for j in range(i + 1, len(bundle_ids)):\n","                bundle1_id = bundle_ids[i]\n","                bundle2_id = bundle_ids[j]\n","                if bundle1_id in bundle_data and bundle2_id in bundle_data:\n","                    bundle1_items = bundle_data[bundle1_id]\n","                    bundle2_items = bundle_data[bundle2_id]\n","                    intersection = len(bundle1_items.intersection(bundle2_items))\n","                    union = len(bundle1_items.union(bundle2_items))\n","                    jaccard_similarity = intersection / union if union > 0 else 0\n","                    jaccard_similarities.append(1 - jaccard_similarity)  # 1-similarity to represent diversity\n","\n","        inter_diversity = sum(jaccard_similarities) / len(jaccard_similarities) if jaccard_similarities else 0\n","        inter_diversity_scores.append({\"user_id\": user_id, \"top_n\": top_n, \"inter_diversity\": inter_diversity})\n","    return inter_diversity_scores"],"metadata":{"id":"As-qpdgrGIDw","executionInfo":{"status":"ok","timestamp":1735799917177,"user_tz":-420,"elapsed":437,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["data_dict"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"id":"W5jfzwYKD21C","executionInfo":{"status":"ok","timestamp":1735524242289,"user_tz":-420,"elapsed":10,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"9f30d4c0-ec78-4178-ff5c-fa5dd7ba7437"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'bundle_final_price': '$4.77',\n"," 'bundle_url': 'http://store.steampowered.com/bundle/594/?utm_source=SteamDB&utm_medium=SteamDB&utm_campaign=SteamDB%20Bundles%20Page',\n"," 'bundle_price': '$5.97',\n"," 'bundle_name': 'The Ninjahtic Series',\n"," 'bundle_id': '594',\n"," 'items': [{'genre': 'Action, Adventure, Indie',\n","   'item_id': '385230',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/385230',\n","   'item_name': 'Ninjahtic'},\n","  {'genre': 'Action, Adventure, Indie',\n","   'item_id': '387880',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/387880',\n","   'item_name': 'Ninjahtic Mind Tricks'},\n","  {'genre': 'Action, Indie',\n","   'item_id': '454130',\n","   'discounted_price': '$1.99',\n","   'item_url': 'http://store.steampowered.com/app/454130',\n","   'item_name': 'Nil-Ninjahtic: Ronin'}],\n"," 'bundle_discount': '20%'}"]},"metadata":{},"execution_count":8}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_knn.json.gz'\n","\n","average_hit_ratio = {}\n","average_intra_diversity = {}\n","average_inter_diversity = {}\n","count = 0\n","\n","top_bundles_results = []\n","hit_ratios = []\n","intra_diversity_scores = []\n","inter_diversity_scores = []\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","\n","                top_bundles_results = get_top_rec_bundles(data_dict)\n","                hit_ratios = calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data)\n","                intra_diversity_scores = calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data)\n","                inter_diversity_scores = calculate_inter_diversity(top_bundles_results, bundle_data)\n","\n","                average_hit_ratio[data_dict['user_id']] = hit_ratios\n","                average_intra_diversity[data_dict['user_id']] = intra_diversity_scores\n","                average_inter_diversity[data_dict['user_id']] = inter_diversity_scores\n","\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","            count += 1\n","            print(f\"{count} /  9881\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"jn67YIwICr93","executionInfo":{"status":"ok","timestamp":1735524265611,"user_tz":-420,"elapsed":23327,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"1632d2a2-60c2-42f3-daa9-b8d648eadcdb","collapsed":true},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n","4883 /  9881\n","4884 /  9881\n","4885 /  9881\n","4886 /  9881\n","4887 /  9881\n","4888 /  9881\n","4889 /  9881\n","4890 /  9881\n","4891 /  9881\n","4892 /  9881\n","4893 /  9881\n","4894 /  9881\n","4895 /  9881\n","4896 /  9881\n","4897 /  9881\n","4898 /  9881\n","4899 /  9881\n","4900 /  9881\n","4901 /  9881\n","4902 /  9881\n","4903 /  9881\n","4904 /  9881\n","4905 /  9881\n","4906 /  9881\n","4907 /  9881\n","4908 /  9881\n","4909 /  9881\n","4910 /  9881\n","4911 /  9881\n","4912 /  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Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_knn.json.gz' successfully processed and saved to '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/tags_and_specs_reranking/reranking_recommendation_data_knn.json.gz'\n","Count: 9880\n"]}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast\n","\n","# Open the gzipped file\n","data_dict = None\n","filepath_rarank_rec_data = '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/Recommendations/price_patterns_reranking/reranking_recommendation_data_knn.json.gz'\n","\n","average_hit_ratio = {}\n","average_intra_diversity = {}\n","average_inter_diversity = {}\n","count = 0\n","\n","top_bundles_results = []\n","hit_ratios = []\n","intra_diversity_scores = []\n","inter_diversity_scores = []\n","\n","try:\n","    with gzip.open(filepath_rarank_rec_data, 'rt', encoding='utf-8') as infile:\n","        for line in infile:\n","            try:\n","                data_dict = json.loads(line) # Use json.loads instead of ast.literal_eval\n","\n","                if len(data_dict[\"rec_bundles\"]) > 0:\n","\n","                  top_bundles_results = get_top_rec_bundles(data_dict)\n","                  hit_ratios = calculate_hit_ratio(top_bundles_results, user_item_interactions, bundle_data)\n","                  intra_diversity_scores = calculate_intra_diversity(top_bundles_results, user_item_interactions, bundle_data)\n","                  inter_diversity_scores = calculate_inter_diversity(top_bundles_results, bundle_data)\n","\n","                  average_hit_ratio[data_dict['user_id']] = hit_ratios\n","                  average_intra_diversity[data_dict['user_id']] = intra_diversity_scores\n","                  average_inter_diversity[data_dict['user_id']] = inter_diversity_scores\n","\n","            except json.JSONDecodeError as e:\n","                print(f\"Error decoding JSON: {e}, skipping line: {line}\")\n","            count += 1\n","            print(f\"{count} /  9881\")\n","    print(f\"File '{filepath_rarank_rec_data}' successfully processed and saved to '{filepath_rarank_rec_data}'\")\n","\n","except FileNotFoundError:\n","    print(f\"Error: File not found at {filepath_rarank_rec_data}\")\n","except Exception as e:\n","    print(f\"An unexpected error occurred: {e}\")\n","\n","print(f\"Count: {count}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"C7CEB5cmvFCZ","executionInfo":{"status":"ok","timestamp":1735799931133,"user_tz":-420,"elapsed":13957,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"5cff4db4-559d-48da-e214-4de34c1f10ab"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1;30;43mStreaming output truncated to the last 5000 lines.\u001b[0m\n","4878 /  9881\n","4879 /  9881\n","4880 /  9881\n","4881 /  9881\n","4882 /  9881\n","4883 /  9881\n","4884 /  9881\n","4885 /  9881\n","4886 /  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               each containing a 'top_n' and a metric value.\n","\n","    Returns:\n","        A pandas DataFrame with the average metrics for each 'top_n'.\n","    \"\"\"\n","\n","    all_metrics = []\n","    for user_id, user_metrics in metrics_dict.items():\n","        all_metrics.extend(user_metrics)\n","\n","    df = pd.DataFrame(all_metrics)\n","\n","    numeric_cols = df.select_dtypes(include=['number']).columns\n","    return df.groupby('top_n')[numeric_cols].mean()\n","\n","# Calculate and print the average hit ratio\n","average_hit_ratio_df = calculate_average_metrics(average_hit_ratio)\n","print(\"Average Hit Ratio:\")\n","print(average_hit_ratio_df)\n","\n","# Calculate and print the average intra-list diversity\n","average_intra_diversity_df = calculate_average_metrics(average_intra_diversity)\n","print(\"\\nAverage Intra-list Diversity:\")\n","print(average_intra_diversity_df)\n","\n","# Calculate and print the average inter-list diversity\n","average_inter_diversity_df = calculate_average_metrics(average_inter_diversity)\n","print(\"\\nAverage Inter-list Diversity:\")\n","average_inter_diversity_df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":501},"id":"r7-DgF7QKIJB","executionInfo":{"status":"ok","timestamp":1735799931452,"user_tz":-420,"elapsed":322,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"e6c230fb-3983-406a-8267-3f31fabd347e"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["Average Hit Ratio:\n","       top_n  hit_ratio\n","top_n                  \n","5        5.0   0.513340\n","10      10.0   0.343921\n","15      15.0   0.247396\n","20      20.0   0.192660\n","\n","Average Intra-list Diversity:\n","       top_n  diversity\n","top_n                  \n","5        5.0   0.995296\n","10      10.0   0.987449\n","15      15.0   0.975292\n","20      20.0   0.969601\n","\n","Average Inter-list Diversity:\n"]},{"output_type":"execute_result","data":{"text/plain":["       top_n  inter_diversity\n","top_n                        \n","5        5.0         0.776677\n","10      10.0         0.774081\n","15      15.0         0.771772\n","20      20.0         0.771809"],"text/html":["\n","  <div id=\"df-4ba62344-94f1-4868-b578-31107bff1d64\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>top_n</th>\n","      <th>inter_diversity</th>\n","    </tr>\n","    <tr>\n","      <th>top_n</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    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average_hit_ratio_df.index:\n","    row = {\n","        'top_n': top_n,\n","        'hit_ratio': average_hit_ratio_df.loc[top_n, 'hit_ratio'],\n","        'intra_diversity': average_intra_diversity_df.loc[top_n, 'diversity'],\n","        'inter_diversity': average_inter_diversity_df.loc[top_n, 'inter_diversity']\n","    }\n","    combined_data.append(row)\n","  return pd.DataFrame(combined_data)\n","\n","# Example usage (assuming the three dataframes are available):\n","combined_df = combine_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df)\n","combined_df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":175},"id":"cdolqR3XOM3R","executionInfo":{"status":"ok","timestamp":1735799931879,"user_tz":-420,"elapsed":3,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"c956e99a-a0cb-4727-8941-7ce18327910b"},"execution_count":11,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   top_n  hit_ratio  intra_diversity  inter_diversity\n","0      5   0.513340         0.995296         0.776677\n","1     10   0.343921         0.987449         0.774081\n","2     15   0.247396         0.975292         0.771772\n","3     20   0.192660         0.969601         0.771809"],"text/html":["\n","  <div id=\"df-f77f871d-4614-404b-aae2-77d39b11a57d\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>top_n</th>\n","      <th>hit_ratio</th>\n","      <th>intra_diversity</th>\n","      <th>inter_diversity</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>5</td>\n","      <td>0.513340</td>\n","      <td>0.995296</td>\n","      <td>0.776677</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>10</td>\n","      <td>0.343921</td>\n","      <td>0.987449</td>\n","      <td>0.774081</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>15</td>\n","      <td>0.247396</td>\n","      <td>0.975292</td>\n","      <td>0.771772</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>20</td>\n","      <td>0.192660</td>\n","      <td>0.969601</td>\n","      <td>0.771809</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f77f871d-4614-404b-aae2-77d39b11a57d')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg 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\"num_unique_values\": 4,\n        \"samples\": [\n          0.3439211822660099,\n          0.19266009852216748,\n          0.5133399014778325\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"intra_diversity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.011621469230349677,\n        \"min\": 0.96960142278235,\n        \"max\": 0.9952963604837032,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          0.9874487550562487,\n          0.96960142278235,\n          0.9952963604837032\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"inter_diversity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0023274631891260535,\n        \"min\": 0.7717715583940074,\n        \"max\": 0.7766774064705099,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          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average_intra_diversity_df, and average_inter_diversity_df\n","# Make it dense space between bars, and change the color of bar for the best value\n","\n","# prompt: generate bar chart for each average_hit_ratio_df, average_intra_diversity_df, and average_inter_diversity_df\n","# Make it dense space between bars, and change the color of bar for the best value\n","\n","import matplotlib.pyplot as plt\n","\n","def plot_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df):\n","    \"\"\"Generates bar charts for average hit ratio, intra-diversity, and inter-diversity.\"\"\"\n","\n","    fig, axes = plt.subplots(3, 1, figsize=(8, 10))  # Adjust figsize as needed\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_hit_ratio_df['hit_ratio'].idxmax()\n","    top_n_values = average_hit_ratio_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Hit Ratio ---\n","    axes[0].bar(average_hit_ratio_df.index, average_hit_ratio_df['hit_ratio'], width=4.0, color=colors)\n","    axes[0].set_xlabel(\"Top N Recommendations\")\n","    axes[0].set_ylabel(\"Average Hit Ratio\")\n","    axes[0].set_title(\"Average Hit Ratio for Different Top N Values\")\n","    axes[0].set_xticks(average_hit_ratio_df.index)\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_intra_diversity_df['diversity'].idxmax()\n","    top_n_values = average_intra_diversity_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Intra-list Diversity ---\n","    axes[1].bar(average_intra_diversity_df.index, average_intra_diversity_df['diversity'], width=4.0, color=colors)\n","    axes[1].set_xlabel(\"Top N Recommendations\")\n","    axes[1].set_ylabel(\"Average Intra-list Diversity\")\n","    axes[1].set_title(\"Average Intra-list Diversity for Different Top N Values\")\n","    axes[1].set_xticks(average_intra_diversity_df.index)\n","\n","    # Find the index of the maximum value\n","    best_value_index = average_inter_diversity_df['inter_diversity'].idxmax()\n","    top_n_values = average_inter_diversity_df.index\n","\n","    colors = ['skyblue'] * len(top_n_values)\n","    colors[top_n_values.get_loc(best_value_index)] = 'green' # Highlight the best value\n","\n","    # --- Inter-list Diversity ---\n","    axes[2].bar(average_inter_diversity_df.index, average_inter_diversity_df['inter_diversity'], width=4.0, color=colors)\n","    axes[2].set_xlabel(\"Top N Recommendations\")\n","    axes[2].set_ylabel(\"Average Inter-list Diversity\")\n","    axes[2].set_title(\"Average Inter-list Diversity for Different Top N Values\")\n","    axes[2].set_xticks(average_inter_diversity_df.index)\n","\n","    plt.tight_layout()  # Adjust layout to prevent overlapping\n","    plt.show()\n","\n","plot_metrics(average_hit_ratio_df, average_intra_diversity_df, average_inter_diversity_df)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"H53yAPjpKxgM","executionInfo":{"status":"ok","timestamp":1735524266965,"user_tz":-420,"elapsed":1039,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"3d5723e3-b0be-4568-fdf5-05e6a9c60ba2"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 800x1000 with 3 Axes>"],"image/png":"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\n"},"metadata":{}}]}]}
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