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A Survey on Aspect Based Opinion Mining

Zalak Kansagra, Sanjay D. Bhanderi

Abstract


Increasing growth and availability of the social media on the World Wide Web, disclosed users choice in form of opinions, reviews, comments, b1ogs and feedbacks on services, people, events, organizations, products etc. These information available on web is discovered to be assistive to various individuals, organizations and governments for decision making. Opinion mining is the study of automatic identification of online user’s preference and classification of these preferences into its positive, negative or neutral orientation. Aspect based opinion mining focus on opinions related to multiple features, components or attributes of various entities like products, services, people etc., that have been presented on web. The main objective of this paper is discover the field of aspect based opinion mining in the area of Natural Language Processing and to represent some of the prominent work that have been carried out in this field. Various challenges and issues that have been found in this field are presented along with the comparative study of various approaches presented in this paper.


Keywords


Machine Learning, Maximum Entropy, Natural Language Processing, Opinion Mining.

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