Abstract
In this paper, we present an opinion mining system to identify product features and opinions from review documents. The features and opinions are extracted using semantic and linguistic analysis of text documents. The polarity of opinion sentences is established using polarity scores of the opinion words through Senti-WordNet to generate a feature-based summary of review documents. The system is also integrated with a visualization module to present feature-based summary of review documents in a comprehendible way.
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© 2009 Springer-Verlag Berlin Heidelberg
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Abulaish, M., Jahiruddin, Doja, M.N., Ahmad, T. (2009). Feature and Opinion Mining for Customer Review Summarization. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_35
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DOI: https://doi.org/10.1007/978-3-642-11164-8_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11163-1
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