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A Novel User Profile Learning Approach with Fuzzy Constraint for News Retrieval
Author(s) -
Chen ShengTao,
Yu TingJung,
Chen LiangChu,
Liu FanPyn
Publication year - 2017
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21840
Subject(s) - computer science , constraint (computer aided design) , fuzzy logic , artificial intelligence , information retrieval , machine learning , mathematics , geometry
This study conducts a novel user profile learning approach based on fuzzy constraints. From the vantage of knowledge representation, a fuzzy constraint network is used not only to present the ambiguity of concepts and the diversity between concepts but also to express a single user profile with dependent multisubjects of interest. From the vantage of problem solving, the construction of a user profile is viewed as a problem of fuzzy constraint satisfaction. The subject of interest is extracted by a spreading activation model. To achieve the information filtering of the retrieved data, fuzzy information gain is employed to reduce unnecessary user feedback for matching the user's retrieval requirements.