Name
Abstract | ||
|---|---|---|
This paper proposes a collaborative filtering system using Improved Fuzzy Associative Memory (IFAM) which readjusts the connection weights between the nodes of FAM using error back propagation and simplifies the Fuzzy rules. The proposed technique automatically recommends high-quality information to users with similar interests on arbitrarily narrow information domains. It asks a user to rate a gauge set of items. It then evaluates the user's rates and suggests a recommendation set of items. The proposed system is implemented in a web server and tested its performance in the domain of retrieval of technical papers, especially in the field of information technologies. The experimental results show that it may piovide reliable recommendations. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1016/S0167-739X(03)00142-0 | Future Generation Comp. Syst. |
Keywords | Field | DocType |
collaborative filtering,improved fuzzy associative memory,reliable recommendation,recommendation item,fam,narrow information domain,connection weight,information technology,fuzzy rule,proposed technique,proposed system,preference,recommendation information,fuzzy,high-quality information,error back propagation,associative memory | Fuzzy associative memory,Data mining,Collaborative filtering,Information retrieval,Information technology,Inference,Computer science,Fuzzy logic,Backpropagation,The Internet,Web server | Journal |
Volume | Issue | ISSN |
20 | 2 | Future Generation Computer Systems |
Citations | PageRank | References |
1 | 0.35 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Won Kim | 1 | 10 | 1.69 |
| Il-Ju Ko | 2 | 17 | 6.53 |
| Jin-Sung Yoon | 3 | 1 | 0.35 |
| Gye-Young Kim | 4 | 116 | 24.67 |