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license: cc-by-4.0
task_categories:
- tabular-classification
- time-series-forecasting
tags:
- time-series-classification
- sequence-modeling
- micro-interactions
- UI-adaptation
- behavioral-modeling
- human-computer-interaction
---
# Dataset Card: Edge-Native Adaptive UI Behavioral Logs
This repository stores aggregated behavioral interaction logs in raw and processed forms, primarily in the `.parquet` data storage format.
These logs support research on edge-native adaptive user interfaces.
## 1. Hosted Data
The repository hosts microtensor parquet files derived from public research datasets and runtime experiment sessions:
- AdSERP Search and Interaction Logs (Arapakis et al., 2025).
- High-Volume Trajectories (Mendeley Mouse Dynamics, 2026).
- Structured Human-Machine Interaction Logs (Carrera-Rivera et al., 2023).
- Client-Side Action Paths (Ou et al., 2021).
- Continuous Kinematics (Leiva and Arapakis, 2020).
### Interim & Sequence Datasets:
- **Canonical Traces (`interim/traces/canonical_traces.parquet`):** Ingested browser experiment telemetry traces (`schemaVersion 1.1.0`) with standard and extended provenance fields (`sessionId`, `experimentId`, `conditionId`, `taskId`, `windowId`, `sourceEventIds`, `preprocessingVersion`, `featureSchemaVersion`).
- **MicroTensor Sequences (`interim/sequences.parquet`):** Model-ready sequential interaction tensors ($T=8$, $D=18$) assembled with strict session and task boundary isolation and lookahead window alignment for `TargetInterventionHead` training.
### Raw Scripted Traces:
- **Verified Testbed Traces (`raw/scripted/`):** 18 verified browser experiment traces (`schemaVersion 1.1.0`) recorded from automated browser sessions across baseline and adaptive conditions, complete with trace validation and window attribution verification (`manifest.json`).
### Processed Datasets:
- **Target Intervention Dataset (`processed/v1.0.0/target_intervention_dataset.parquet`, `processed/target_intervention_dataset.parquet`):** Target-domain dataset with 289 examples pairing sequential MicroTensors ($T=8$, $D=18$) and canonical UIContext vectors ($\mathbb{R}^6$) with 5-class intervention labels (`no_op`, `highlight_primary_action`, `simplify_options`, `expand_tooltip`, `offer_assistance`) generated via Scripted Intervention Label Policy v1.0.0 (ADR-013). Accompanied by provenance-versioned `manifest.json` detailing SHA-256 trace digests, class distributions, and session-bounded train/val/test splits.
## 2. References
For full details on the data preprocessing pipeline, MicroTensor feature schema, and target outcome taxonomy, refer to the following repositories:
- **Model Preparation Repository:** [taofeeqhamzat/edge-aui-model-preparation](https://github.com/taofeeqhamzat/edge-aui-model-preparation)
- **Framework Repository:** [taofeeqhamzat/edge-aui](https://github.com/taofeeqhamzat/edge-aui)
Please refer to the source repositories for detailed technical specifications and training guidelines.
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