Abstract
Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras
| Original language | English |
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| Title of host publication | 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI '06): Proceedings: 18-22 December, 2006, Hong Kong, China |
| Publisher | IEEE |
| Number of pages | 5 |
| ISBN (Print) | 0769527477 |
| Publication status | Published - 2006 |
| Event | International Joint Conference on Web Intelligence and Intelligent Agent Technology - Duration: 1 Jan 2006 → … |
Conference
| Conference | International Joint Conference on Web Intelligence and Intelligent Agent Technology |
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| Period | 1/01/06 → … |
Keywords
- consumer goods
- reviews
- information filtering systems
- consumer behavior
- recommender systems (information filtering)
- digital cameras