Paper: Extracting Opinion Targets and Opinion Words from Online Reviews with Graph Co-ranking

ACL ID P14-1030
Title Extracting Opinion Targets and Opinion Words from Online Reviews with Graph Co-ranking
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Extracting opinion targets and opinion words from online reviews are two fun- damental tasks in opinion mining. This paper proposes a novel approach to col- lectively extract them with graph co- ranking. First, compared to previous methods which solely employed opinion relations among words, our method con- structs a heterogeneous graph to model two types of relations, including seman- tic relations and opinion relations. Next, a co-ranking algorithm is proposed to es- timate the confidence of each candidate, and the candidates with higher confidence will be extracted as opinion targets/words. In this way, different relations make coop- erative effects on candidates? confidence estimation. Moreover, word preference is captured and incorporated into our co- ranking algorithm. In this way, o...