聊天中的话题检测与提取

Paige Adams, C. Martell
{"title":"聊天中的话题检测与提取","authors":"Paige Adams, C. Martell","doi":"10.1109/ICSC.2008.61","DOIUrl":null,"url":null,"abstract":"Internet-based Chat environments such as Internet relay Chat and instant messaging pose a challenge for data mining and information retrieval systems due to the multi-threaded, overlapping nature of the dialog and the nonstandard usage of language. In this paper we present preliminary methods of topic detection and topic thread extraction that augment a typical TF-IDF-based vector space model approach with temporal relationship information between posts of the Chat dialog combined with WordNet hypernym augmentation. We show results that promise better performance than using only a TF-IDF bag-of-words vector space model.","PeriodicalId":102805,"journal":{"name":"2008 IEEE International Conference on Semantic Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"93","resultStr":"{\"title\":\"Topic Detection and Extraction in Chat\",\"authors\":\"Paige Adams, C. Martell\",\"doi\":\"10.1109/ICSC.2008.61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Internet-based Chat environments such as Internet relay Chat and instant messaging pose a challenge for data mining and information retrieval systems due to the multi-threaded, overlapping nature of the dialog and the nonstandard usage of language. In this paper we present preliminary methods of topic detection and topic thread extraction that augment a typical TF-IDF-based vector space model approach with temporal relationship information between posts of the Chat dialog combined with WordNet hypernym augmentation. We show results that promise better performance than using only a TF-IDF bag-of-words vector space model.\",\"PeriodicalId\":102805,\"journal\":{\"name\":\"2008 IEEE International Conference on Semantic Computing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-08-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"93\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Semantic Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSC.2008.61\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Semantic Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSC.2008.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 93

摘要

基于Internet的聊天环境,如Internet中继聊天和即时消息传递,由于对话的多线程、重叠性质和语言的非标准使用,对数据挖掘和信息检索系统提出了挑战。在本文中,我们提出了主题检测和主题线程提取的初步方法,该方法将聊天对话框帖子之间的时间关系信息与WordNet超词增强相结合,增强了典型的基于tf - idf的向量空间模型方法。我们展示的结果承诺比仅使用TF-IDF词袋向量空间模型更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topic Detection and Extraction in Chat
Internet-based Chat environments such as Internet relay Chat and instant messaging pose a challenge for data mining and information retrieval systems due to the multi-threaded, overlapping nature of the dialog and the nonstandard usage of language. In this paper we present preliminary methods of topic detection and topic thread extraction that augment a typical TF-IDF-based vector space model approach with temporal relationship information between posts of the Chat dialog combined with WordNet hypernym augmentation. We show results that promise better performance than using only a TF-IDF bag-of-words vector space model.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信