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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

Preprocessing and Feature Selection Approach for Efficient Sentiment Analysis on Product Reviews

verfasst von : Monalisa Ghosh, Gautam Sanyal

Erschienen in: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Verlag: Springer Singapore

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Abstract

In the recent years opinion mining plays an important role by business analyst before launching a product. Opinion mining mainly concerns about detecting and extracting the feature from various opinion rich resources like review sites, discussion forum, blogs and news corpora so on. The data obtained from those are highly unstructured in nature and very large in volume, therefore data preprocessing plays an essential role in sentiment analysis. Researchers are trying to develop newer algorithm. This research paper attempts to develop a better opinion mining algorithm and the performance has been worked out.

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Metadaten
Titel
Preprocessing and Feature Selection Approach for Efficient Sentiment Analysis on Product Reviews
verfasst von
Monalisa Ghosh
Gautam Sanyal
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications

Print ISBN: 978-981-10-3152-6

Electronic ISBN: 978-981-10-3153-3

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-3153-3_72

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