Multiple Factors-Based Opinion Retrieval and Coarse-to-Fine Sentiment Classification

Opinion mining is a growing interest task in both research and practical applications. It deals with the computational treatment of opinion, sentiment, and subjectivity in documents. This paper focuses on retrieving the opinion documents and giving their sentiment orientation. Mining and ranking the topic relevant opinion documents are implemented with a sentiment model, combining the existing knowledge and statistic information. Multi-level sentiment analysis approach is proposed to find the topic related sentiment information. Our experimental results on COAE show the effectiveness of the proposed techniques and the feasibility of classifying orientation at varying levels of granularity.