Improve the effectiveness of the opinion retrieval and opinion polarity classification

Opinion retrieval is a document retrieving and ranking process. A relevant document must be relevant to the query and contain opinions toward the query. Opinion polarity classification is an extension of opinion retrieval. It classifies the retrieved document as positive, negative or mixed, according to the overall polarity of the query relevant opinions in the document. This paper (1) proposes several new techniques that help improve the effectiveness of an existing opinion retrieval system; (2) presents a novel two-stage model to solve the opinion polarity classification problem. In this model, every query relevant opinionated sentence in a document retrieved by our opinion retrieval system is classified as positive or negative respectively by a SVM classifier. Then a second classifier determines the overall opinion polarity of the document. Experimental results show that both the opinion retrieval system with the proposed opinion retrieval techniques and the polarity classification model outperformed the best reported systems respectively. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Searc