Translated Title
A text opinion retrieval method based on knowledge graph
Translated Abstract
Text opinion retrieval aims at finding relevant and opinionate documents according to a user’s query.User queries are usually too short to describe the information need accurately.Knowledge Graph is a structured semantic knowledge base,which the information of knowledge graph can help us to describe the information need.In this paper, we propose a text opinion retrieval method based on knowledge graph.Firstly,we get the candidate of query expansion terms by knowledge graph,and calculate four kinds of features of each candidate named term distributions,co-occur-rence frequency,proximity and collection frequency.Then,we choose the expansion terms by SVM classifier with the features.Finally,we expand the generative opinion retrieval model using the expansion terms to get the opinion retrieval result.Experimental results on Sina Microblog and Twitter datasets show that our proposed method obtains significant improvements in terms of MAP and NDCG over the baseline approaches.
Translated Keyword
knowledge graph
opinion retrieval
query expansion
Access Number
WF:perioarticalsddxxb201611005
