Applied data mining to product reviews - Ghorashi, Seyed Hamid
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Companies and manufacturers selling their products on the web are usually looking for a way to collect reviews and feedback from their customers about the products or associated services. Assuredly, it is noteworthy for them to get the public opinion about their productions, so that they can increase the popularity of their merchandises. Gathering these opinions is not a tough task and it could be achieved easily by making an Internet website and then asking from the customers to comment on the product features through the website. The difficulty of this solution is occurred while the business…mehr

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Produktbeschreibung
Companies and manufacturers selling their products on the web are usually looking for a way to collect reviews and feedback from their customers about the products or associated services. Assuredly, it is noteworthy for them to get the public opinion about their productions, so that they can increase the popularity of their merchandises. Gathering these opinions is not a tough task and it could be achieved easily by making an Internet website and then asking from the customers to comment on the product features through the website. The difficulty of this solution is occurred while the business holders decide to review all these comments and extract the feasible weakness or strength of their product or particular features of that product. Sometimes a feature might be interesting for one, while it does not make that impression for someone else. This study compared three different pattern mining algorithms and determined the most efficient one that can be applied in our opinion mining system.
Autorenporträt
Seyed Hamid Ghorashi, received his master's degree in Computer Science from University of Technology, Malaysia in 2012. His research interests include Data mining, Machine Learning, Knowledge Extraction and Organization.