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Ranking Entity Based on Both of Word Frequency and Word Sematic Features

2016-08-03
Xiao-Bo Jin, Guang-Gang Geng, Kaizhu Huang, Zhi-Wei Yan

Abstract

Entity search is a new application meeting either precise or vague requirements from the search engines users. Baidu Cup 2016 Challenge just provided such a chance to tackle the problem of the entity search. We achieved the first place with the average MAP scores on 4 tasks including movie, tvShow, celebrity and restaurant. In this paper, we propose a series of similarity features based on both of the word frequency features and the word semantic features and describe our ranking architecture and experiment details.

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URL

https://arxiv.org/abs/1608.01068

PDF

https://arxiv.org/pdf/1608.01068


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