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Leveraging interlingual classification to improve web search
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
In this paper we address the problem of improving accuracy of web search in a smaller, data-limited search market (search language) using behavioral data from a larger, datarich market (assist language). Specifically, we use interlingual classification to infer the search language query's intent using the assist language click-through data. We use these improved estimates of query intent, along with the query intent based on the search language data, to compute features that encode the
doi:10.1145/2187980.2188114
dblp:conf/www/JagarlamudiBS12
fatcat:vxofrdgsvbdyhix6csfyyi6q4y