LEARNING FUZZY USER PROFILES FOR RESOURCE RECOMMENDATION

被引：8

作者：

Castellano, Giovanna ^{[1
]}

Castiello, Ciro ^{[1
]}

Dell'Agnello, Danilo ^{[1
]}

Fanelli, Anna Maria ^{[1
]}

Mencar, Corrado ^{[1
]}

Torsello, Maria Alessandra ^{[1
]}

机构：

[1] Univ Bari Aldo Moro, Dept Comp Sci, I-70125 Bari, Italy

来源：

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2010年 / 18卷 / 04期

关键词：

User profile; recommender systems; fuzzy set theory; fuzzy metadata; Movie-Lens dataset; OF-THE-ART; WEB; PERSONALIZATION; SYSTEMS;

D O I：

10.1142/S0218488510006611

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Recommender systems are systems capable of assisting users by quickly providing them with relevant resources according to their interests or preferences. The efficacy of a accesses. The adaption of the preference profile is performed continuously, but inearlier stages it is more sensitive to updates(plastic phase)while in later stages it is less sensitive (stable phase) to allow resource recommendation. Simulation results are reported to show the effectiveness of the proposed approach

引用

页码：389 / 410

页数：22

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