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Paper Details
Paper Title
Evaluate spam detection using hybrid technique of Support Vector Mechine
Authors
  Kishan Thumar,  Prof. Dulari Bosamiya
Abstract
Due to the social media, online reviews are widely adopted. They greatly impact consumer’s purchasing decisions. A slight difference in a business rating on a review website can significantly change the reputation of them. Review spamming is quite common on many online shopping platforms like Amazon. In this work a hybrid method is used to detect whether a review is spam or not. From previous studies it is found that SVM(Support Vector Machine) gives comparatively good result for this task. PSO (Particle Swarm Optimization) is the optimization technique which can be used improve the result of SVM. Here duplicate detection is used after preprocessing of data to find if two reviews are same or not. After that feature identification is done and then PSO is used to choose the population and these values are used in SVM to classify reviews. Hence in this work, a Hybrid classifier (SVM+PSO) to classify review as a spam or not spam is used.
Keywords- Data mining, Web mining, Review Spam, Review Spammer, Support vector machine(SVM), Particle swarm optimization(PSO)
Publication Details
Unique Identification Number - IJEDR1504143Page Number(s) - 807-811Pubished in - Volume 3 | Issue 4 | December 2015DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Kishan Thumar,  Prof. Dulari Bosamiya,   "Evaluate spam detection using hybrid technique of Support Vector Mechine", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 4, pp.807-811, December 2015, Available at :http://www.ijedr.org/papers/IJEDR1504143.pdf
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