TY - JOUR
T1 - Exploiting formal concept analysis in a customizing recommendation for new user and gray sheep problems
AU - Li, Xiaohui
AU - Murata, Tomohiro
PY - 2012
Y1 - 2012
N2 - Recommender systems are becoming an indispensable application and re-shaping the world in e-commerce scopes. This paper reviews the major problems in the existing recommender systems and presents a tracking recommendation approach based on information of user's behavior and two-level property of items. A new recommendation model based the synergistic use of knowledge from repository, which includes user's behavior, and items property was constructed and utilizes the Formal Concept Analysis (FCA) mapping to guide a personalized recommendation for user. We simulate a prototype recommender system that can make the quality recommendation by tracking user's behavior for implementing the proposed approach and testing its performance. Experiments using two datasets show our strategy was more robust against the drawbacks and preponderate over traditional recommendation approaches in cold-start conditions.
AB - Recommender systems are becoming an indispensable application and re-shaping the world in e-commerce scopes. This paper reviews the major problems in the existing recommender systems and presents a tracking recommendation approach based on information of user's behavior and two-level property of items. A new recommendation model based the synergistic use of knowledge from repository, which includes user's behavior, and items property was constructed and utilizes the Formal Concept Analysis (FCA) mapping to guide a personalized recommendation for user. We simulate a prototype recommender system that can make the quality recommendation by tracking user's behavior for implementing the proposed approach and testing its performance. Experiments using two datasets show our strategy was more robust against the drawbacks and preponderate over traditional recommendation approaches in cold-start conditions.
KW - Behavior tracking
KW - Formal concept analysis
KW - Knowledge repository
KW - Recommender system
UR - http://www.scopus.com/inward/record.url?scp=84867019050&partnerID=8YFLogxK
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U2 - 10.1541/ieejeiss.132.782
DO - 10.1541/ieejeiss.132.782
M3 - Article
AN - SCOPUS:84867019050
VL - 132
SP - 782
EP - 789
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
SN - 0385-4221
IS - 5
ER -