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題名 A Recommender Mechanism Based on Case-Based Reasoning
作者 楊亨利
Wang, Chen-Shu;Yang, Heng-Li
貢獻者 資管系
關鍵詞 Recommender mechanism;Case-based reasoning;Multiple stage reasoning;Genetic algorithm;Artificial intelligence application
日期 2012.03
上傳時間 13-Nov-2014 15:07:57 (UTC+8)
摘要 Case-based reasoning (CBR) algorithm is particularly suitable for solving ill-defined and unstructured decision-making problems in many different areas. The traditional CBR algorithm, however, is inappropriate to deal with complicated problems and therefore needs to be further revised. This study thus proposes a next-generation CBR (GCBR) model and algorithm. GCBR presents as a new problem-solving paradigm that is a case-based recommender mechanism for assisting decision making. GCBR can resolve decision-making problems by using hierarchical criteria architecture (HCA) problem representation which involves multiple decision objectives on each level of hierarchical, multiple-level decision criteria, thereby enables decision makers to identify problems more precisely. Additionally, the proposed GCBR can also provide decision makers with series of cases in support of these multiple decision-making stages. GCBR furthermore employs a genetic algorithm in its implementation in order to reduce the effort involved in case evaluation. This study found experimentally that using GCBR for making travel-planning recommendations involved approximately 80% effort than traditional CBR, and therefore concluded that GCBR should be the next generation of case-based reasoning algorithms and can be applied to actual case-based recommender mechanism implementation.
關聯 Expert Systems with Applications, 39(4), 4335-4343
資料類型 article
DOI http://dx.doi.org/http://dx.doi.org/10.1016/j.eswa.2011.09.161
dc.contributor 資管系en_US
dc.creator (作者) 楊亨利zh_TW
dc.creator (作者) Wang, Chen-Shu;Yang, Heng-Lien_US
dc.date (日期) 2012.03en_US
dc.date.accessioned 13-Nov-2014 15:07:57 (UTC+8)-
dc.date.available 13-Nov-2014 15:07:57 (UTC+8)-
dc.date.issued (上傳時間) 13-Nov-2014 15:07:57 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/71374-
dc.description.abstract (摘要) Case-based reasoning (CBR) algorithm is particularly suitable for solving ill-defined and unstructured decision-making problems in many different areas. The traditional CBR algorithm, however, is inappropriate to deal with complicated problems and therefore needs to be further revised. This study thus proposes a next-generation CBR (GCBR) model and algorithm. GCBR presents as a new problem-solving paradigm that is a case-based recommender mechanism for assisting decision making. GCBR can resolve decision-making problems by using hierarchical criteria architecture (HCA) problem representation which involves multiple decision objectives on each level of hierarchical, multiple-level decision criteria, thereby enables decision makers to identify problems more precisely. Additionally, the proposed GCBR can also provide decision makers with series of cases in support of these multiple decision-making stages. GCBR furthermore employs a genetic algorithm in its implementation in order to reduce the effort involved in case evaluation. This study found experimentally that using GCBR for making travel-planning recommendations involved approximately 80% effort than traditional CBR, and therefore concluded that GCBR should be the next generation of case-based reasoning algorithms and can be applied to actual case-based recommender mechanism implementation.en_US
dc.format.extent 1137660 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Expert Systems with Applications, 39(4), 4335-4343en_US
dc.subject (關鍵詞) Recommender mechanism;Case-based reasoning;Multiple stage reasoning;Genetic algorithm;Artificial intelligence applicationen_US
dc.title (題名) A Recommender Mechanism Based on Case-Based Reasoningen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.eswa.2011.09.161en_US
dc.doi.uri (DOI) http://dx.doi.org/http://dx.doi.org/10.1016/j.eswa.2011.09.161en_US