Method with large-scale evaluation · 2009

Collaborative Filtering with Temporal Dynamics

Koren Y

What it found

People's preferences drift over time. Models that track that drift, instead of treating old data like new, predicted ratings on a large Netflix dataset better than anything reported before.

Where the evidence stops

Movie ratings, not daily behaviour. No decay rate carries over.

How it shapes Pursue

Pursue

What you tell Pursue today outranks a pattern from last month.

A design input, not evidence that Pursue works.

Cited in

  1. 01How can an app help me if it doesn't know me yet?By asking, briefly, instead of guessing. A 2023 systematic review (Yuan and Hernandez) treats the 'cold start', a new user with no history, as its own problem, and asking the person directly is one approach that works from the first day. Later, fresh answers should outweigh old patterns, because preferences drift (Koren, 2009).Learning a person

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