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

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.

The paper decribes the apporoaches that help us to achieve the first place in Baidu Cup 2016 NLP Challenge