{"title":"一种基于大规模网络词典的词库构建方法","authors":"Kotaro Nakayama, T. Hara, S. Nishio","doi":"10.1109/AINA.2007.23","DOIUrl":null,"url":null,"abstract":"Web-based dictionaries, such as Wikipedia, have become dramatically popular among the Internet users in past several years. The important characteristic of Web-based dictionary is not only the huge amount of articles, but also hyperlinks. Hyperlinks have various information more than just providing transfer function between pages. In this paper, we propose an efficient method to analyze the link structure of Web-based dictionaries to construct an association thesaurus. We have already applied it to Wikipedia, a huge scale Web-based dictionary which has a dense link structure, as a corpus. We developed a search engine for evaluation, then conducted a number of experiments to compare our method with other traditional methods such as cooccurrence analysis.","PeriodicalId":361109,"journal":{"name":"21st International Conference on Advanced Information Networking and Applications (AINA '07)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":"{\"title\":\"A Thesaurus Construction Method from Large ScaleWeb Dictionaries\",\"authors\":\"Kotaro Nakayama, T. Hara, S. Nishio\",\"doi\":\"10.1109/AINA.2007.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web-based dictionaries, such as Wikipedia, have become dramatically popular among the Internet users in past several years. The important characteristic of Web-based dictionary is not only the huge amount of articles, but also hyperlinks. Hyperlinks have various information more than just providing transfer function between pages. In this paper, we propose an efficient method to analyze the link structure of Web-based dictionaries to construct an association thesaurus. We have already applied it to Wikipedia, a huge scale Web-based dictionary which has a dense link structure, as a corpus. We developed a search engine for evaluation, then conducted a number of experiments to compare our method with other traditional methods such as cooccurrence analysis.\",\"PeriodicalId\":361109,\"journal\":{\"name\":\"21st International Conference on Advanced Information Networking and Applications (AINA '07)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"49\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"21st International Conference on Advanced Information Networking and Applications (AINA '07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINA.2007.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on Advanced Information Networking and Applications (AINA '07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2007.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Thesaurus Construction Method from Large ScaleWeb Dictionaries
Web-based dictionaries, such as Wikipedia, have become dramatically popular among the Internet users in past several years. The important characteristic of Web-based dictionary is not only the huge amount of articles, but also hyperlinks. Hyperlinks have various information more than just providing transfer function between pages. In this paper, we propose an efficient method to analyze the link structure of Web-based dictionaries to construct an association thesaurus. We have already applied it to Wikipedia, a huge scale Web-based dictionary which has a dense link structure, as a corpus. We developed a search engine for evaluation, then conducted a number of experiments to compare our method with other traditional methods such as cooccurrence analysis.