A frequent pattern mining algorithm for feature extraction of customer reviews
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 part...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
IJCSI Publisher
2012
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| Subjects: | |
| 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 |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | 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. |
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