2008 BypassRatesReducingQueryAbandon

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We introduce a new approach to analyzing click logs by examining both the documents that are clicked and those that are bypassed-documents returned higher in the ordering of the search results but skipped by the user. This approach complements the popular click-through rate analysis, and helps to draw negative inferences in the click logs. We formulate a natural objective that finds sets of results that are unlikely to be collectively bypassed by a typical user. This is closely related to the problem of reducing query abandonment. We analyze a greedy approach to optimizing this objective, and establish theoretical guarantees of its performance. We evaluate our approach on a large set of queries, and demonstrate that it compares favorably to the maximal marginal relevance approach on a number of metrics including mean average precision and mean reciprocal rank.



 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2008 BypassRatesReducingQueryAbandonAtish Das Sarma
Sreenivas Gollapudi
Samuel Ieong
Bypass Rates: Reducing Query Abandonment Using Negative InferencesKDD-2008 Proceedings10.1145/1401890.14019162008