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題名 Two Stages of Case-Based Reasoning --- Integrating Genetic Algorithm with Data Mining Mechanisms
作者 楊亨利;Cheng-Shu Wang
Yang, Heng-Li
關鍵詞 Case-base reasoning; Case retrieve; Genetic algorithm; KDD
日期 2008-07
上傳時間 17-Jan-2009 15:59:07 (UTC+8)
摘要 Case-based reasoning (CBR) is a paradigm, concept and instinctive mechanism for problem solving. Recently, CBR has been widely integrated with some AI algorithms and applied to various kinds of problems. The ill-defined and unstructured problems are suitably solved by CBR. This research proposes a hybrid CBR mechanism including two stages. In stage I, the genetic algorithm is adopted to improve efficiency of case retrieving process. Compared to traditional CBR, the proposed mechanism could reduce about 14% case evaluations, but still achieved 90% satisfactory results. In stage II, the knowledge discovering and data mining (KDD) processes are implemented to produce the refined information from the retrieved cases. Because these retrieved cases and target problem satisfy similar or even same conditions, the outcome of KDD would be more valuable for reference. In addition to retrieved cases of stage I, the proposed mechanism provides direction and relevant knowledge for decision makers in their decision supporting and revising processes in stage II. The proposed CBR mechanism also deals with efficiency and outcome quality issues of traditional CBR.
關聯 Expert Systems with Applications: An International Journal , 35(1/2), 262-272
資料類型 article
DOI http://dx.doi.org/http://dx.doi.org/10.1016/j.eswa.2007.06.027
dc.creator (作者) 楊亨利;Cheng-Shu Wangzh_TW
dc.creator (作者) Yang, Heng-Li-
dc.date (日期) 2008-07en_US
dc.date.accessioned 17-Jan-2009 15:59:07 (UTC+8)-
dc.date.available 17-Jan-2009 15:59:07 (UTC+8)-
dc.date.issued (上傳時間) 17-Jan-2009 15:59:07 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/26979-
dc.description.abstract (摘要) Case-based reasoning (CBR) is a paradigm, concept and instinctive mechanism for problem solving. Recently, CBR has been widely integrated with some AI algorithms and applied to various kinds of problems. The ill-defined and unstructured problems are suitably solved by CBR. This research proposes a hybrid CBR mechanism including two stages. In stage I, the genetic algorithm is adopted to improve efficiency of case retrieving process. Compared to traditional CBR, the proposed mechanism could reduce about 14% case evaluations, but still achieved 90% satisfactory results. In stage II, the knowledge discovering and data mining (KDD) processes are implemented to produce the refined information from the retrieved cases. Because these retrieved cases and target problem satisfy similar or even same conditions, the outcome of KDD would be more valuable for reference. In addition to retrieved cases of stage I, the proposed mechanism provides direction and relevant knowledge for decision makers in their decision supporting and revising processes in stage II. The proposed CBR mechanism also deals with efficiency and outcome quality issues of traditional CBR.-
dc.format application/en_US
dc.language enen_US
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Expert Systems with Applications: An International Journal , 35(1/2), 262-272en_US
dc.subject (關鍵詞) Case-base reasoning; Case retrieve; Genetic algorithm; KDD-
dc.title (題名) Two Stages of Case-Based Reasoning --- Integrating Genetic Algorithm with Data Mining Mechanismsen_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/j.eswa.2007.06.027en_US
dc.doi.uri (DOI) http://dx.doi.org/http://dx.doi.org/10.1016/j.eswa.2007.06.027en_US