Implicit data collection
Implicit data collection refers to techniques in human–computer interaction and recommender systems that infer user preferences from observed behavior rather than explicit input.
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| Concepts |
| Methods and challenges |
| Implementations |
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Implicit data collection refers to techniques in human–computer interaction and recommender systems that infer user preferences from observed behavior rather than explicit input.[1]
Overview
[edit]Implicit data are used to construct a user model from interaction traces such as clicks, purchases, or dwell time. These signals enable information filtering and personalization in recommender systems and search.[2]
In recommender systems, implicit feedback is often modeled through techniques such as matrix factorization and pairwise ranking, which treat user interactions as positive-only or preference signals.[3][4]
Data sources
[edit]Implicit signals include behavioral and contextual data, such as:
- interaction logs (clicks, views, purchases)
- dwell time and browsing patterns
- contextual and device information
- multimodal signals (e.g., gaze, voice, or facial expression)
These signals are typically noisy and require modeling assumptions to distinguish preference from exposure.[5]
References
[edit]- ^ Ricci, Francesco; Rokach, Lior; Shapira, Bracha (2015). Recommender Systems Handbook. Springer. doi:10.1007/978-1-4899-7637-6.
- ^ Joachims, Thorsten (2002). "Optimizing Search Engines Using Clickthrough Data". Proceedings of the ACM SIGKDD Conference. doi:10.1145/775047.775067.
- ^ Hu, Yifan; Koren, Yehuda; Volinsky, Chris (2008). "Collaborative Filtering for Implicit Feedback Datasets". Proceedings of the IEEE International Conference on Data Mining. doi:10.1109/ICDM.2008.22.
- ^ Rendle, Steffen; Freudenthaler, Christoph; Gantner, Zeno; Schmidt-Thieme, Lars (2009). "BPR: Bayesian Personalized Ranking from Implicit Feedback". Proceedings of the Conference on Uncertainty in Artificial Intelligence. doi:10.48550/arXiv.1205.2618.
- ^ Hu, Yifan; Koren, Yehuda; Volinsky, Chris (2008). "Collaborative Filtering for Implicit Feedback Datasets". Proceedings of the IEEE International Conference on Data Mining.