{"title":"Information retrieval by text summarization for an Indian regional language","authors":"Jagadish S. Kallimani, K. Srinivasa, B. E. Reddy","doi":"10.1109/NLPKE.2010.5587764","DOIUrl":null,"url":null,"abstract":"The Information Extraction is a method for filtering information from large volumes of text. Information Extraction is a limited task than full text understanding. In full text understanding, we aspire to represent in an explicit fashion about all the information in a text. In contrast, in Information Extraction, we delimit in advance, as part of the specification of the task and the semantic range of the output. In this paper, a model for summarization from large documents using a novel approach has been proposed. Extending the work for an Indian regional language (Kannada) and various analyses of results were discussed.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NLPKE.2010.5587764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 23
Abstract
The Information Extraction is a method for filtering information from large volumes of text. Information Extraction is a limited task than full text understanding. In full text understanding, we aspire to represent in an explicit fashion about all the information in a text. In contrast, in Information Extraction, we delimit in advance, as part of the specification of the task and the semantic range of the output. In this paper, a model for summarization from large documents using a novel approach has been proposed. Extending the work for an Indian regional language (Kannada) and various analyses of results were discussed.
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