Abstract
Mining opinions from online reviews is a fundamental step in obtaining the overall sentiment of a product. Detection of opinion relations among the words play an important role in the opinion target (OT) and opinion word (OW) extraction. In this paper, Partially Supervised Word Alignment Model is used to find opinion relations among words. Graph based co-ranking algorithm is used in estimating the confidence of each OT and OW. Candidates having confidence value higher than the threshold are extracted as final OT and OW. We propose a hybrid method that considers semantic relations along with opinion relations that results in fine grained opinion target (OT) and opinion word (OW) extraction. This semantic relations and opinion relations affects the confidence calculation of the OT and OW and improves the precision of extraction.
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