Using adaptive resonance theory and data-mining techniques for materials recommendation based on the e-library environment

The Electronic Library

Volumn 26, Issue 3, 2008, Pages 287-302

  Tsai, Chwei Shyong ^a   Chen, Mu Yen ^b  

^a NATIONAL CHUNG HSING UNIVERSITY   (Taiwan)

^b NATIONAL CHANGHUA UNIVERSITY OF EDUCATION   (Taiwan)

Author keywords

Artificial intelligence; Computer based learning; Databases; Libraries; Neural nets

Indexed keywords

ARTIFICIAL INTELLIGENCE; ARTS COMPUTING; BACKPROPAGATION; BIONICS; COMPUTER NETWORKS; DIGITAL ARITHMETIC; FILTER BANKS; INTELLIGENT MATERIALS; LIBRARIES; METROPOLITAN AREA NETWORKS; MINING; MINING ENGINEERING; NETWORK PROTOCOLS; NEURAL NETWORKS; PIGMENTS; RESONANCE; SURVEYS; TECHNOLOGY;

ADAPTIVE RESONANCE THEORY (ART1); APPLIED (CO); APRIORI ALGORITHMS; APRIORI MINING TECHNIQUES; ARTIFICIAL NEURAL NETWORK (ANNS); DATA-SETS; DEMOGRAPHIC VARIABLES; DESIGN/METHODOLOGY/APPROACH; DIGITAL CONTENTS; DIGITAL INFORMATIONS; LIBRARY USERS; MINING RESULTS; MINING TECHNIQUES; QUESTIONNAIRE SURVEYS; READERS (USER EXPERIENCE); RECOMMENDER SYSTEMS;

DIGITAL LIBRARIES;

EID: 45349086254     PISSN: 02640473     EISSN: None     Source Type: Journal    
DOI: 10.1108/02640470810879455     Document Type: Article

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