Informed recommender: Basing recommendations on consumer product reviews
- Publication Type:
- Journal Article
- Citation:
- IEEE Intelligent Systems, 2007, 22 (3), pp. 39 - 47
- Issue Date:
- 2007-05-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
 | 2006011397.pdf | 328.73 kB |
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An Informed recommender has been developed that uses prioritized consumer product reviews to make recommendations and maps each piece of review comment using text mining techniques. The recommender uses ontology that provides a controlled vocabulary and relationships among words to describe the consumer's skill level and experience with the product in the review comment in the system. The recommender process involves the useful information to be useful for the recommendation process. The recommender system makes a recommendation based on the ontology data, and therefore, recommendation quality depends on accurately mapping the proper knowledge from the semantic features in the review comments. When a user requests an evaluation of a particular product based on certain features, the overall feature quality is calculated from reviews containing the valuation of this feature.
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