Name
Abstract | ||
|---|---|---|
In this paper a fuzzy-based recommendation method is presented. Its main goal is to improve the recommendation recall maintaining high recommendation precision. The formal model has been built to describe the method and to analyze how the measures used in traditional Information Retrieval may be adapted to evaluate the effectiveness of recommendation process. The original contributions consist among others of proving several properties which show that the method is able to adapt to changing user's needs and achieving the maximum effectiveness if the component methods work properly. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.3233/IFS-2009-0418 | Journal of Intelligent and Fuzzy Systems |
Keywords | Field | DocType |
recommendation process,high recommendation precision,original contribution,maximum effectiveness,recall value,main goal,recommender system,fuzzy-based recommendation method,component method,fuzzy-based method,formal model,traditional Information Retrieval | Recommender system,Fuzzy logic,Artificial intelligence,Recall,Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
20 | 1 | 1064-1246 |
Citations | PageRank | References |
0 | 0.34 | 8 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maciej Kiewra | 1 | 46 | 6.14 |
| Ngoc Thanh Nguyen | 2 | 1875 | 184.23 |