A Unified Graph Model for Sentence-Based Opinion Retrieval

There is a growing research interest in opinion retrieval as on-line users' opinions are becoming more and more popular in business, social networks, etc. Practically speaking, the goal of opinion retrieval is to retrieve documents, which entail opinions or comments, relevant to a target subject specified by the user's query. A fundamental challenge in opinion retrieval is information representation. Existing research focuses on document-based approaches and documents are represented by bag-of-word. However, due to loss of contextual information, this representation fails to capture the associative information between an opinion and its corresponding target. It cannot distinguish different degrees of a sentiment word when associated with different targets. This in turn seriously affects opinion retrieval performance. In this paper, we propose a sentence-based approach based on a new information representation, namely topic-sentiment word pair, to capture intra-sentence conte...

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Binyang Li, Lanjun Zhou, Shi Feng, Kam-Fai Wong
• Keywords: ACL 2010, Computational Linguistics, Graph-based Model, Information, Opinion Retrieval