政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/71374

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 109948/140897 (78%)
Visitors : 46102479 Online Users : 945

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 > Item 140.119/71374

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/71374

Title:	A Recommender Mechanism Based on Case-Based Reasoning
Authors:	楊亨利 Wang, Chen-Shu;Yang, Heng-Li
Contributors:	資管系
Keywords:	Recommender mechanism;Case-based reasoning;Multiple stage reasoning;Genetic algorithm;Artificial intelligence application
Date:	2012.03
Issue Date:	2014-11-13 15:07:57 (UTC+8)
Abstract:	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.
Relation:	Expert Systems with Applications, 39(4), 4335-4343
Data Type:	article
DOI 連結:	http://dx.doi.org/http://dx.doi.org/10.1016/j.eswa.2011.09.161
DOI:	10.1016/j.eswa.2011.09.161
Appears in Collections:	[資訊管理學系] 期刊論文

Files in This Item:

File	Description	Size	Format
4335-4343.pdf		1110Kb	Adobe PDF2	879	View/Open

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

Loading...