{"title":"Domain-specific Information Retrieval system with a correspondence graph","authors":"A. Azarian, A. Siadat, J. Bauchat","doi":"10.1109/ICDIM.2007.4444191","DOIUrl":null,"url":null,"abstract":"This paper describes different existing solutions and proposes a new approach for information retrieval with request specified in natural language within a specific domain and in a multilingual context. The experimental platform employed was the SIDIS- Enterprise car-diagnosis System of Siemens AG (Germany). The paper proposes a new methodology to retrieve car failures symptoms and is based on a correspondence graph. This methodology is more based on perception than on similarity computation between request and symptoms. A comparison study between this approach and usual retrieval methods (e.g. term frequency based) provide promising results.","PeriodicalId":198626,"journal":{"name":"2007 2nd International Conference on Digital Information Management","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 2nd International Conference on Digital Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDIM.2007.4444191","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
This paper describes different existing solutions and proposes a new approach for information retrieval with request specified in natural language within a specific domain and in a multilingual context. The experimental platform employed was the SIDIS- Enterprise car-diagnosis System of Siemens AG (Germany). The paper proposes a new methodology to retrieve car failures symptoms and is based on a correspondence graph. This methodology is more based on perception than on similarity computation between request and symptoms. A comparison study between this approach and usual retrieval methods (e.g. term frequency based) provide promising results.