Study on the method of precise entity search based on Baidu’s query

Abstract

For a given query, searching for entities that conform to the description facts in the given set, in view of this goal, this paper proposes a matching method based on classification and semantic extension. The algorithm firstly to classify the query string into three categories, and extract the key word of different categories of query word. Then the keyword is extended to get the matching word set based on the word2vec word vector model. At last we calculate the score of every entity by the weighted matching method and get results according to the score ranking. After the experiment, the method get the correct rate of 63.2%, which has good applicability, and to a certain extent, it reduces the retrieval failure rate due to the query of the spoken language and diversification.