Zheng Chen, Shengping Liu, Wenyin Liu, G. Pu, Wei-Ying Ma
{"title":"从网络链接结构建立一个网络词典","authors":"Zheng Chen, Shengping Liu, Wenyin Liu, G. Pu, Wei-Ying Ma","doi":"10.1145/860435.860447","DOIUrl":null,"url":null,"abstract":"Thesaurus has been widely used in many applications, including information retrieval, natural language processing, and question answering. In this paper, we propose a novel approach to automatically constructing a domain-specific thesaurus from the Web using link structure information. The proposed approach is able to identify new terms and reflect the latest relationship between terms as the Web evolves. First, a set of high quality and representative websites of a specific domain is selected. After filtering out navigational links, link analysis is applied to each website to obtain its content structure. Finally, the thesaurus is constructed by merging the content structures of the selected websites. The experimental results on automatic query expansion based on our constructed thesaurus show 20% improvement in search precision compared to the baseline.","PeriodicalId":209809,"journal":{"name":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"80","resultStr":"{\"title\":\"Building a web thesaurus from web link structure\",\"authors\":\"Zheng Chen, Shengping Liu, Wenyin Liu, G. Pu, Wei-Ying Ma\",\"doi\":\"10.1145/860435.860447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thesaurus has been widely used in many applications, including information retrieval, natural language processing, and question answering. In this paper, we propose a novel approach to automatically constructing a domain-specific thesaurus from the Web using link structure information. The proposed approach is able to identify new terms and reflect the latest relationship between terms as the Web evolves. First, a set of high quality and representative websites of a specific domain is selected. After filtering out navigational links, link analysis is applied to each website to obtain its content structure. Finally, the thesaurus is constructed by merging the content structures of the selected websites. The experimental results on automatic query expansion based on our constructed thesaurus show 20% improvement in search precision compared to the baseline.\",\"PeriodicalId\":209809,\"journal\":{\"name\":\"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"80\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/860435.860447\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/860435.860447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thesaurus has been widely used in many applications, including information retrieval, natural language processing, and question answering. In this paper, we propose a novel approach to automatically constructing a domain-specific thesaurus from the Web using link structure information. The proposed approach is able to identify new terms and reflect the latest relationship between terms as the Web evolves. First, a set of high quality and representative websites of a specific domain is selected. After filtering out navigational links, link analysis is applied to each website to obtain its content structure. Finally, the thesaurus is constructed by merging the content structures of the selected websites. The experimental results on automatic query expansion based on our constructed thesaurus show 20% improvement in search precision compared to the baseline.