{"title":"An intelligent component retrieval system using conversational CBR","authors":"Mingyang Gu, Xin Tong","doi":"10.1109/CMPSAC.2004.1342670","DOIUrl":null,"url":null,"abstract":"One difficulty in component retrieval comes from users' incapability to well define their queries. In this paper, we propose a conversational component retrieval model (CCRM) to alleviate this difficulty. In CCRM, a knowledge-intensive conversational case-based reasoning method is adopted to infer potential knowledge from current known knowledge, calculate the context-based semantic similarities between users' queries and stored components, and prompt users the most discriminative questions to extract more information to refine their component queries interactively and incrementally.","PeriodicalId":355273,"journal":{"name":"Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th Annual International Computer Software and Applications Conference, 2004. COMPSAC 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMPSAC.2004.1342670","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
One difficulty in component retrieval comes from users' incapability to well define their queries. In this paper, we propose a conversational component retrieval model (CCRM) to alleviate this difficulty. In CCRM, a knowledge-intensive conversational case-based reasoning method is adopted to infer potential knowledge from current known knowledge, calculate the context-based semantic similarities between users' queries and stored components, and prompt users the most discriminative questions to extract more information to refine their component queries interactively and incrementally.