Topics in Data Science/Өгөгдлийн шинжлэх ухаан

Page 1. Topics in Data Science / Өгөгдлийн шинжлэх ухаан Rutgers University has made this article freely available. Please share how this access benefits you. Your story matters. [https://rucore.libraries.rutgers.edu/rutgers-lib/52378/story/] …


I Boukhris, Z Elouedi, M Ajabi - Knowledge and Information Systems, 2017

Page 1. Knowl Inf Syst DOI 10.1007/s10115-017-1034-4 REGULAR PAPER Toward intrusion detection using belief decision trees for big data Imen Boukhris1 · Zied Elouedi1 · Mariem Ajabi1 Received: 3 December 2015 / Accepted ...


Towards Accurate Duplicate Bug Retrieval Using Deep Learning Techniques

J Deshmukh, S Podder, S Sengupta, N Dubash - Software Maintenance and …, 2017

… Each word in the dictionary was then mapped to its corresponding embedding. We experimented with both GloVe vectors trained3 on Common Crawl dataset as well as Word2Vec vectors trained4 on Google news dataset. We …


Towards Automatic Identification of Fake News: Headline-Article Stance Detection with LSTM Attention Models

... 3 Page 4. of Wikipedia and Common Crawl. We further created a randomly initialized UNK vector of zeros, for words that were not found in the GloVe set. 5.4 LSTM Attention Architectures 5.4.1 Conditionally Encoded (CE) LSTMs ...


Towards Automatically Evaluating Security Risks and Providing Cyber Intelligence

Page 1. TOWARDS AUTOMATICALLY EVALUATING SECURITY RISKS AND PROVIDING CYBER INTELLIGENCE A Thesis Presented to The Academic Faculty by Xiaojing Liao In Partial Fulfillment of the Requirements for ...


Towards Document-Level Neural Machine Translation

Page 1. TROPE R HCRAESE R PAID I TOWARDS DOCUMENT-LEVEL NEURAL MACHINE TRANSLATION Lesly Miculicich Werlen Idiap-RR-25-2017 SEPTEMBER 2017 Centre du Parc, Rue Marconi 19, PO Box 592, CH ...


Towards Semantic Query Segmentation

A Kale, T Taula, S Hewavitharana, A Srivastava - arXiv preprint arXiv:1707.07835, 2017

... estimators. This process was repeated with pretrained GloVe vectors on common crawl [14] and facebook fasttext [2] pretrained model over Wikipedia corpus with 2.5M word vocabulary. 2 shows the experiment results. We ...


Towards the ImageNet-CNN of NLP: Pretraining Sentence Encoders with Machine Translation

B McCann, J Bradbury, C Xiong, R Socher - Advances in Neural Information …, 2017

… When training an MT-LSTM, we used fixed 300-dimensional word vectors. We used the CommonCrawl-840B GloVe model for English word vectors, which were completely fixed during training, so that the MT-LSTM had to learn how to use the pretrained vectors for translation …


TraininG towards a society of data-saVvy inforMation prOfessionals to enable open leadership INnovation

T Blume, F Böschen, L Galke, A Saleh, A Scherp - 2017

Page 1. Deliverable 3.1: Technologies for MOVING data processing and visualisation v1.0 Till Blume, Falk Böschen, Lukas Galke, Ahmed Saleh, Ansgar Scherp, Matthias Schulte-Althoff/ZBW Chrysa Collyda, Vasileios Mezaris, Alexandros Pournaras, Christos Tzelepis/CERTH ...


Translation Quality and Productivity: A Study on Rich Morphology Languages

L Specia, K Harris, F Blain, A Burchardt, V Macketanz…

... This process resulted in: • EN–DE: Over 20 million generic and in-domain sentence pairs obtained by merging the datasets available in the OPUS (Tiedemann, 2012), TAUS, WMT and JRC 3 repositories (eg Europarl, CDEP, CommonCrawl, etc.); ...


Translation Quality Estimation Using only bilingual Corpora

L Liu, A Fujita, M Utiyama, A Finch, E Sumita - IEEE/ACM Transactions on Audio, …, 2017

... languages. As the bilingual corpora for conducting M2LE training, we employed Europarl and Common Crawl provided by WMT13 for the WMT15 and WMT14 tasks and a Japanese–Chinese bilingual corpus [9] for the JA2ZH task. ...


TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation

... We use the publicly available D = 300 dimensional GloVe4 (trained using 42B tokens from the Common Crawl) and CBOW5 (trained using 100B tokens from Google News) embeddings as the word representations required by TSP. ...


Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension

D Golub, PS Huang, X He, L Deng - arXiv preprint arXiv:1706.09789, 2017

... We initialize word-embeddings for the BIDAF model, answer synthesis module, and question synthesis module with 300-dimensional-GloVe vectors (Pennington et al., 2014) trained on the 840B Common Crawl corpus. We set all embeddings of unknown word tokens to zero. ...


Two-Step MT: Predicting Target Morphology

F Burlot, E Knyazeva, T Lavergne, F Yvon - 2016

... from TED training set Full TED set (117k) + QED (242k) + europarl (885k) + news-commentary (1M) Monolingual data (various subsets ranging from 5M to 200M): Target side of the biggest parallel corpus Czeng-1.6-pre subtitles news corpora (WMT'16) common-crawl (WMT'16 ...


Unbounded cache model for online language modeling with open vocabulary

E Grave, M Cisse, A Joulin - arXiv preprint arXiv:1711.02604, 2017

... In the following, we refer to this dataset as commentary. • Common Crawl is a text dataset collected from diverse web sources. The dataset is shuffled at the sentence level. ... [9] C. Buck, K. Heafield, and B. van Ooyen. N-gram counts and language models from the common crawl...


Understanding and Predicting the Usefulness of Yelp Reviews

... I concatenate output from both RNNs to make the final prediction. (figure 1) [1] https://www.yelp. com/dataset_challenge [2] Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors): glove.42B.300d.zip from http://nlp.stanford.edu/projects/glove/ Page 4. ...


Understanding Regional Context of World Wide Web using Common Crawl Corpus

Abstract—The World Wide Web has emerged as the most important and essential tool for the society. Today, people heavily rely on rich resources available in the web for communication, business, maps, and social networking etc. In addition, people seek web


Understanding Spreadsheet Evolution in Practice

L Xu - Software Maintenance and Evolution (ICSME), 2017 …, 2017

… IEEE International Conference on Software Engineering (ICSE), 2015, pp. 7– 16. [28] “Common crawl data on AWS.” [Online]. Available: http://aws.amazon.com/datasets/ 41740. [29] C. Chambers, M. Erwig, and M. Luckey, “SheetDiff …


Unsupervised Neural Machine Translation

M Artetxe, G Labaka, E Agirre, K Cho - arXiv preprint arXiv:1710.11041, 2017

... For that purpose, we used the combination of all parallel corpora provided at WMT 2014, which comprise Europarl, Common Crawl and News Commentary for both language pairs plus the UN and the Gigaword corpus for FrenchEnglish. ...


Using Distributional Semantics for Automatic Taxonomy Induction

... system. They used general and domain specific corpora such as GigaWord, ukWac etc. and the common crawl to extract lexico-syntactic patterns. Additionally, they applied pruning methods to refine the generated taxonomy. ...


Using images to improve machine-translating e-commerce product listings

I Calixto, D Stein, E Matusov, P Lohar, S Castilho… - EACL 2017, 2017

... Table 2 we show the number of running words as well as the perplexity scores obtained with LMs trained on three sets of different German corpora: the Multi30k, eBay's in-domain data and a concatenation of the WMT 20152 Europarl (Koehn, 2005), Common Crawl and News ...


Using Recurrent Neural Network to Predict The Usefulness of Yelp Reviews

... The frequency of alternation is a hyper-parameter Figure 2: MTL RNN structure with detailed input and output description [2] Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors): glove.42B.300d.zip from http://nlp.stanford.edu/projects/glove/ Page 4. ...


UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings

... GloVe Model-Tweets (GV-T), Wikipedia + Gigaword (GV-WG), Common Crawl 42B tokens (GV-CC1), Common Crawl 840B tokens (GV-CC2): GloVe is similar to Word2Vec, in that it obtains dense vector representations of words. ...


Page 1. Variable length word encodings for neural translation models Jiameng Gao Department of Engineering University of Cambridge This dissertation is submitted for the degree of Master of Philosophy Peterhouse August 11, 2016 Page 2. Page 3. Page 4. Page 5. ...


VecShare: A Framework for Sharing Word Representation Vectors

... we utilize three sets of GloVe embeddings (Pennington et al., 2014): wik+, 100-dimensional embeddings trained on six billion tokens of Wikipedia and the Gigaword corpus; web, 300-dimensional embeddings trained on 42 billion tokens of the Common Crawl Web dataset ...


Page 1. Masaryk University Faculty of Informatics Vector Space Representations in Information Retrieval Master's Thesis Vít Novotný Brno, Fall 2017 Page 2. Page 3. Masaryk University Faculty of Informatics Vector Space Representations in Information Retrieval Master's Thesis …


Visual Exploration of High-Dimensional Spaces Through Identification, Summarization, and Interpretation of Two-Dimensional Projections. Abstract. With the ever-increasing amount of available computing resources and sensing ...


Visually Grounded Word Embeddings and Richer Visual Features for Improving Multimodal Neural Machine Translation

JB Delbrouck, S Dupont, O Seddati - arXiv preprint arXiv:1707.01009, 2017

... to. As previously mentioned, the textual representation lwi is obtained with the word embeddings algorithm Glove. We use the pre-trained model on the Common Crawl corpus consisting of 840B tokens and a 2.2M words. The ...


Web-scale profiling of semantic annotations in HTML pages

... In 2012, the Common Crawl Foundation (CC)8 started to continuously release crawled web corpora of a decent size and made them publicly available. Each of the corpora contains several tera-bytes of compressed HTML pages. ...


Web-Scale Web Table to Knowledge Base Matching

… 43 4.2.1 Common Crawl … Page 20. 12 CHAPTER 1. INTRODUCTION 1.4 Published Work Parts of the work presented in this thesis have been published previously: • The extraction of the WDC Web Table Corpus from the Common Crawl …


What's good for the goose is good for the GANder

... To reduce the percentage of un- known words, we additionally brought down the size of our vocabulary to contain only the 10k most commonly used words in the training set; and used GloVe vectors (Pennington et al., 2014), pretrained on Common Crawl (having around 42B ...


Word Embeddings for Practical Information Retrieval

L Galke, A Saleh, A Scherp - INFORMATIK 2017, 2017

... 2 zbw.eu/stw 3 A dataset of crawled web data from https://commoncrawl.org/ Word Embeddings for Similarity Scoring in Practical Information Retrieval 2161 Page 8. i “proceedings” — 2017/8/24 — 12:20 — page 2162 — #2162 i i i ...


Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes

N Garg, L Schiebinger, D Jurafsky, J Zou - arXiv preprint arXiv:1711.08412, 2017

… nearly identical correlation. We further validate this association using different embeddings trained on Wikipedia and Common Crawl texts instead of Google News; see Appendix Section B.1 for details. Google News embedding …


Word Re-Embedding via Manifold Dimensionality Retention

S Hasan, E Curry - Proceedings of the 2017 Conference on Empirical …, 2017

... Original Embedding Spaces. The original word embeddings used are pre-trained GloVe models: Wikipedia 2014 + Gigaword 5 (6B tokens, 400K vocab, 50d, 100d, 200d, & 300d vectors), and Common Crawl (42B tokens, 1.9M vocab, 300d vectors) (Pennington et al., 2014b). ...


Word vectors, reuse, and replicability: Towards a community repository of large-text resources

... Moreover, with an ac- curacy of 83.08 for the semantic analogies, the GloVe model trained on the lemmatized version of Wikipedia outperforms the GloVe model trained on 42 billion tokens of web data from the Common Crawl reported in (Pennington et al., 2014), which at an ...