History repeats itself: repeat queries in Yahoo's logs
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Information re-retrieval: repeat queries in Yahoo's logs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Large scale analysis of web revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Resonance on the web: web dynamics and revisitation patterns
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Large scale query log analysis of re-finding
Proceedings of the third ACM international conference on Web search and data mining
Understanding cyclic trends in social choices
Proceedings of the fifth ACM international conference on Web search and data mining
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We study the patterns by which a user consumes the same item repeatedly over time, in a wide variety domains ranging from check-ins at the same business location to re-watches of the same video. We find that recency of consumption is the strongest predictor of repeat consumption. Based on this, we develop a model by which the item from $t$ timesteps ago is reconsumed with a probability proportional to a function of t. We study theoretical properties of this model, develop algorithms to learn reconsumption likelihood as a function of t, and show a strong fit of the resulting inferred function via a power law with exponential cutoff. We then introduce a notion of item quality, show that it alone underperforms our recency-based model, and develop a hybrid model that predicts user choice based on a combination of recency and quality. We show how the parameters of this model may be jointly estimated, and show that the resulting scheme outperforms other alternatives.