{"title":"基于简单文本挖掘的关键字提取用于业务信息检索","authors":"Xiangzhu Gao, S. Murugesan, Bruce W. N. Lo","doi":"10.1109/ICEBE.2005.66","DOIUrl":null,"url":null,"abstract":"Much of business information is text and the information is subject to frequent changes. The use of efficient and effective mechanisms to retrieve required business information is a key to business success, and automated processing of text to extract key terms is an essential component of such an information retrieval (IR) system. Traditional text processing methods based on complex linguistic or statistic techniques are not efficient in dealing with frequently changing business information and do not necessarily provide satisfying IR results. We propose a simple method to extract important terms (keyterms) from text for application in different aspects of IR and show through experimentation that its performance is comparable to or better than complex methods","PeriodicalId":118472,"journal":{"name":"IEEE International Conference on e-Business Engineering (ICEBE'05)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Extraction of keyterms by simple text mining for business information retrieval\",\"authors\":\"Xiangzhu Gao, S. Murugesan, Bruce W. N. Lo\",\"doi\":\"10.1109/ICEBE.2005.66\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Much of business information is text and the information is subject to frequent changes. The use of efficient and effective mechanisms to retrieve required business information is a key to business success, and automated processing of text to extract key terms is an essential component of such an information retrieval (IR) system. Traditional text processing methods based on complex linguistic or statistic techniques are not efficient in dealing with frequently changing business information and do not necessarily provide satisfying IR results. We propose a simple method to extract important terms (keyterms) from text for application in different aspects of IR and show through experimentation that its performance is comparable to or better than complex methods\",\"PeriodicalId\":118472,\"journal\":{\"name\":\"IEEE International Conference on e-Business Engineering (ICEBE'05)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on e-Business Engineering (ICEBE'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEBE.2005.66\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on e-Business Engineering (ICEBE'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEBE.2005.66","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extraction of keyterms by simple text mining for business information retrieval
Much of business information is text and the information is subject to frequent changes. The use of efficient and effective mechanisms to retrieve required business information is a key to business success, and automated processing of text to extract key terms is an essential component of such an information retrieval (IR) system. Traditional text processing methods based on complex linguistic or statistic techniques are not efficient in dealing with frequently changing business information and do not necessarily provide satisfying IR results. We propose a simple method to extract important terms (keyterms) from text for application in different aspects of IR and show through experimentation that its performance is comparable to or better than complex methods