I. Lodhi, K. Hasan, U. Hasan, N. Mahmood, T. Yoshida, M. A. Anwar
{"title":"案例推理系统中检索过程的优化与神经网络自适应","authors":"I. Lodhi, K. Hasan, U. Hasan, N. Mahmood, T. Yoshida, M. A. Anwar","doi":"10.1109/INMIC.2003.1416750","DOIUrl":null,"url":null,"abstract":"The retrieval process in case based reasoning systems (CBR) is a two-step process. It starts with a problem description and ends when a best matching previous case(s) has/have been retrieved. To optimize the retrieval process, enhancement of both processes is required. This research work explores the use of XML (Extensible Markup Language) as a case descriptive language. An additional goal is to identify factors which play a major role in the optimization process. This work also presents an experimental investigation concerning the use of artificial neural networks in the adaptation process of CBR systems. A backpropagation feedforward neural network in different configurations, has been employed to carry out empirical analysis of using this technique for case based adaptation.","PeriodicalId":253329,"journal":{"name":"7th International Multi Topic Conference, 2003. INMIC 2003.","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimizing retrieval process and using neural networks for adaptation process in case based reasoning systems\",\"authors\":\"I. Lodhi, K. Hasan, U. Hasan, N. Mahmood, T. Yoshida, M. A. Anwar\",\"doi\":\"10.1109/INMIC.2003.1416750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The retrieval process in case based reasoning systems (CBR) is a two-step process. It starts with a problem description and ends when a best matching previous case(s) has/have been retrieved. To optimize the retrieval process, enhancement of both processes is required. This research work explores the use of XML (Extensible Markup Language) as a case descriptive language. An additional goal is to identify factors which play a major role in the optimization process. This work also presents an experimental investigation concerning the use of artificial neural networks in the adaptation process of CBR systems. A backpropagation feedforward neural network in different configurations, has been employed to carry out empirical analysis of using this technique for case based adaptation.\",\"PeriodicalId\":253329,\"journal\":{\"name\":\"7th International Multi Topic Conference, 2003. INMIC 2003.\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"7th International Multi Topic Conference, 2003. INMIC 2003.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INMIC.2003.1416750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Multi Topic Conference, 2003. INMIC 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INMIC.2003.1416750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing retrieval process and using neural networks for adaptation process in case based reasoning systems
The retrieval process in case based reasoning systems (CBR) is a two-step process. It starts with a problem description and ends when a best matching previous case(s) has/have been retrieved. To optimize the retrieval process, enhancement of both processes is required. This research work explores the use of XML (Extensible Markup Language) as a case descriptive language. An additional goal is to identify factors which play a major role in the optimization process. This work also presents an experimental investigation concerning the use of artificial neural networks in the adaptation process of CBR systems. A backpropagation feedforward neural network in different configurations, has been employed to carry out empirical analysis of using this technique for case based adaptation.