Name
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. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/WI.2006.144 | Web Intelligence |
Keywords | Field | DocType |
recommender system,opinions selection,comprehensive mechanism,new recommender system,consumer review,consumer product reviews,case study,prioritizing mechanism,consumer preference,consumer product review,consumer behavior,consumer products,electronic commerce,consumer behaviour,internet,consumer goods,data mining | Recommender system,Data mining,World Wide Web,Computer science,Consumer behaviour,Product reviews,The Internet | Conference |
ISBN | Citations | PageRank |
0-7695-2747-7 | 23 | 1.56 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Silvana Aciar | 1 | 107 | 8.02 |
| Debbie Zhang | 2 | 129 | 8.05 |
| Simeon Simoff | 3 | 542 | 72.16 |
| John Debenham | 4 | 238 | 17.03 |