naa a22 4500 510798667 CHVBK 20180411083345.0 cr unu---uuuuu 180411e20131001xx s 000 0 eng 10.1007/s11277-013-1097-9 doi (NATIONALLICENCE)springer-10.1007/s11277-013-1097-9 The Adaptive Ontology-Based Personalized Recommender System [Elektronische Daten] [Sheng-Tzong Cheng, Chih-Lun Chou, Gwo-Jiun Horng] Recommender systems provide strategies that help users search or make decisions within the overwhelming information spaces nowadays. They have played an important role in various areas such as e-commerce and e-learning. In this paper, we propose a hybrid recommendation strategy of content-based and knowledge-based methods that are flexible for any field to apply. By analyzing the past rating records of every user, the system learns the user's preferences. After acquiring users' preferences, the semantic search-and-discovery procedure takes place starting from a highly rated item. For every found item, the system evaluates the Interest Intensity indicating to what degree the user might like it. Recommender systems train a personalized estimating module using a genetic algorithm for each user, and the personalized estimating model helps improve the precision of the estimated scores. With the recommendation strategies and personalization strategies, users may have better recommendations that are closer to their preferences. In the latter part of this paper, a real-world case, a movie-recommender system adopting proposed recommendation strategies, is implemented. Springer Science+Business Media New York, 2013 Recommender systems nationallicence Hybrid recommender systems nationallicence Content-based filtering nationallicence Knowledge-based systems nationallicence Semantic web nationallicence Ontologies nationallicence Personalization nationallicence Genetic algorithm nationallicence Cheng Sheng-Tzong Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut Chou Chih-Lun Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut Horng Gwo-Jiun Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut Wireless Personal Communications Springer US; http://www.springer-ny.com 72/4(2013-10-01), 1801-1826 0929-6212 72:4<1801 2013 72 11277 https://doi.org/10.1007/s11277-013-1097-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11277-013-1097-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cheng Sheng-Tzong Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut NATIONALLICENCE 700 1- Chou Chih-Lun Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut NATIONALLICENCE 700 1- Horng Gwo-Jiun Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan aut NATIONALLICENCE 773 0- Wireless Personal Communications Springer US; http://www.springer-ny.com 72/4(2013-10-01), 1801-1826 0929-6212 72:4<1801 2013 72 11277 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer