Title :
Customizing knowledge-based recommender system by tracking analysis of user behavior
Author :
Li, Xiaohui ; Murata, Tomohiro
Author_Institution :
Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyusyu, Japan
Abstract :
In this paper, we reviewed the major problems in the existing recommender systems and presented a tracking recommender approach based on user´s behavior information and two-level property of items. Our proposed approach defined user profile model, knowledge resources model and constructed Formal Concept Analysis (FCA) mapping to guide a personalized recommendation for user. We simulated a prototype recommender system that can make the quality recommendation by tracking user´s behavior. The experimental result showed our strategy was more robust against the drawbacks and preponderant than conventional recommender systems.
Keywords :
consumer behaviour; customer profiles; data analysis; electronic commerce; knowledge based systems; product customisation; recommender systems; FCA mapping; e-commerce; formal concept analysis; knowledge resources model; knowledge-based recommender system; mass customization; personalized recommendation; quality recommendation; tracking analysis; tracking recommender; two-level item property; user behavior; user profile model; Adaptation model; Book reviews; Real time systems; Customizing recommendation; behavior tracking; formal concept analysis; knowledge repository;
Conference_Titel :
Industrial Engineering and Engineering Management (IE&EM), 2010 IEEE 17Th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6483-8
DOI :
10.1109/ICIEEM.2010.5646618