A frequent pattern mining algorithm for feature extraction of customer reviews

• Main Authors: Ghorashi, Seyed Hamid, Ibrahim, Roliana, Noekhah, Shirin, Dastjerdi, Niloufar Salehi
• Format: Article
• Published: IJCSI Publisher 2012
• Subjects: HD Industries. Land use. Labor; QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/30391/; http://www.ijcsi.org/articles/A-frequent-pattern-mining-algorithm-for-feature-extraction-of-customer-reviews.php
• Institution: Universiti Teknologi Malaysia

Online shoppers often have different idea about the same product. They look for the product features that are consistent with their goal. Sometimes a feature might be interesting for one, while it does not make that impression for someone else. Unfortunately, identifying the target product with particular features is a tough task which is not achievable with existing functionality provided by common websites. In this paper, we present a frequent pattern mining algorithm to mine a bunch of reviews and extract product features. Our experimental results indicate that the algorithm outperforms the old pattern mining techniques used by previous researchers.