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Paper Details
Paper Title
A Probabilistic Approach to Study Features in Opinion Mining using Fuzzy Selection
Authors
Mrunal Pendharkar, Sweta Kale
Abstract
Opinion mining (also called as sentiment analysis) aims to understand people's thinking towards entities such as products like mobiles, etc. In opinion mining, an opinion word, or feature in short, extracts a thing or a feature of an entity on which users state their views. The proposed model is a new approach to the recognition of such features from unstructured textual reviews. The opinion features are assigned weights or frequency which is used to state the nature of reviews. It is, thus, important to extract the specific opinionated features from text reviews and associate them to opinions.
Using Fuzzy selection techniques, the extracted words are set under a range of 0 to 1 which improves accuracy in sentiment analysis. Finally, after finding an association set of opinion words and product words, the web based application which crawls reviews from websites , posts the classification of reviews.
Keywords- Information search and retrieval, opinion mining, sentiment analysis, natural language processing, fuzzy selection.
Publication Details
Unique Identification Number - IJEDR1503043Page Number(s) - Pubished in - Volume 3 | Issue 3 | July 2015DOI (Digital Object Identifier) - Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
Mrunal Pendharkar, Sweta Kale, "A Probabilistic Approach to Study Features in Opinion Mining using Fuzzy Selection", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 3, pp., July 2015, Available at :http://www.ijedr.org/papers/IJEDR1503043.pdf
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