Topic 06
Learning a person
How a system can help someone it barely knows yet, and why fresh answers beat old patterns.
A system that doesn't know someone yet does badly if it guesses. Asking briefly is one of the few approaches that works from the first day.
Preferences drift, so fresh answers should outweigh old patterns, and what a person ignores is a weak signal of what they don't want.
5 sources
What this topic rests on
- 2023User Cold Start Problem in Recommendation Systems: A Systematic ReviewYuan H, Hernandez AA · IEEE Access 11:136958–136977Affiliation not yet confirmedSystematic review
- 2009Collaborative Filtering with Temporal DynamicsKoren Y · Proceedings of KDD 2009, 447–456Yahoo! ResearchMethod with large-scale evaluation
- 2026Negative Sampling in Recommendation: A Survey and Future DirectionsMa H, Xie R, Meng L, Feng F, Du X, Sun X, Kang Z, Meng X · ACM Transactions on Information Systems 44:1–44Shandong University · Tencent · University of Science and Technology of ChinaSurvey
- 2020Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical ActivityLiao P, Greenewald K, Klasnja P, Murphy S · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4(1):18University of Michigan · IBM Research · Harvard UniversityLearning algorithm with a pilot deployment
- 2025Using Personalized Intervention Criteria in a Mobile Just-in-Time Adaptive Intervention for Increasing Physical Activity in University Students: Pilot StudyIkegaya M, Foo JC, Murata T, Oshima K, Kim J · JMIR Human Factors 12:e66750Shizuoka University · University of Alberta · Heidelberg UniversityPilot study, two groups
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