Scalable user intent mining using a multimodal restricted boltzmann machine
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United States of America Patent
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Mar 6, 2018
Grant Date -
Jun 30, 2016
app pub date -
Dec 31, 2014
filing date -
Dec 31, 2014
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Abstract
A method for scalable user intent mining is provided. The method includes detecting named entities from a plurality of query logs in a public query log dataset and generating features of the plurality of query logs based on the detected named entities. The method also includes applying a multimodal restricted boltzmann machine (RBM) on the generated features of the plurality of query logs to train a public multimodal RBM and generating a plurality of public query representations. Further, the method includes receiving a search query from a user, determining whether there are a plurality of history queries of the user. When there is no history query, user intent is predicted using the public multimodal RBM. When there are the history queries, the public multimodal RBM is applied on the plurality of history queries to train a personalized multimodal RBM, and the user intent is predicted using the personalized multimodal RBM.
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