Domain Specific Opinion Retrieval

Opinion retrieval is a novel information retrieval task and has attracted a great deal of attention with the rapid increase of online opinionated information. Most previous work adopts the classical two stage framework, i.e., first retrieving topic relevant documents and then re-ranking them according to opinion relevance. However, none has considered the problem of domain coherence between queries and topic relevant documents. In this work, we propose to address this problem based on the similarity measure of the usage of opinion words (which users employ to express opinions). Our work is based on the observation that the opinion words are domain dependent. We reformulate this problem as measuring the opinion similarity between domain opinion models of queries and document opinion models. Opinion model is constructed to capture the distribution of opinion words. The basic idea is that if a document has high opinion similarity with a domain opinion model, it indicates that it is not only opinionated but also in the same domain with the query (i.e., domain coherence). Experimental results show that our approach performs comparatively with the state-of-the-art work.