Thursday 28th of March 2024
 

A Frequent Pattern Mining Algorithm for Feature Extraction of Customer Reviews


Seyed Hamid Ghorashi, Roliana Ibrahim, Shirin Noekhah and Niloufar Salehi Dastjerdi

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.

Keywords: association rule, pattern mining, product feature, text mining, data mining

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ABOUT THE AUTHORS

Seyed Hamid Ghorashi
Seyed Hamid Ghorashi is a PhD candidate in computer science at university of technology Malaysia (UTM). His research interests are data mining, text mining, and opinion mining. Hamid received his bachelor in computer hardware from university of Kashan, in 2006 and his master in computer science from university technology of Malaysia in 2012.

Roliana Ibrahim
Roliana Ibrahim is a senior lecturer at the Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia. She received her PhD in System Science from Loughborough University and currently a member of Software Engineering Research Group. Her research interests are the adoption of system thinking methodologies and ontology as innovative solutions for complex systems integration and development, data warehousing and data mining.

Shirin Noekhah
Shirin Noekhah received her BSc in Software Engineering from Islamic Azad University of Najaf Abad, Iran and MSc in Computer Science from University Technology Malaysia (UTM), Malaysia. Her research interests include Soft Computing and its Applications, Software reliability.

Niloufar Salehi Dastjerdi
Niloufar Salehi Dastjerdi received her B.Sc. degree in Software Computer Engineering from Azad University of Najafabad, Iran (IAUN) in 2007, and M.Sc. degree in Computer Science from University Technology Malaysia (UTM) in 2012. Her research interests include Natural Language Processing (NLP), Opinion Mining, Text mining and Data Mining.


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