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2009
ACM

Mining broad latent query aspects from search sessions

11 years 5 months ago
Mining broad latent query aspects from search sessions
Search queries are typically very short, which means they are often underspecified or have senses that the user did not think of. A broad latent query aspect is a set of keywords that succinctly represents one particular sense, or one particular information need, that can aid users in reformulating such queries. We extract such broad latent aspects from query reformulations found in historical search session logs. We propose a framework under which the problem of extracting such broad latent aspects reduces to that of optimizing a formal objective function under constraints on the total number of aspects the system can store, and the number of aspects that can be shown in response to any given query. We present algorithms to find a good set of aspects, and also to pick the best k aspects matching any query. Empirical results on real-world search engine logs show significant gains over a strong baseline that uses single-keyword reformulations: a gain of 14% and 23% in terms of human-ju...
Xuanhui Wang, Deepayan Chakrabarti, Kunal Punera
Added 25 Nov 2009
Updated 25 Nov 2009
Type Conference
Year 2009
Where KDD
Authors Xuanhui Wang, Deepayan Chakrabarti, Kunal Punera
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