CUTS:基于曲率的开发模式分析和博客和其他文本流的分割

Yan Qi, Compo Sci, Eng Dept, K. Selçuk, Candan Sci Comp
{"title":"CUTS:基于曲率的开发模式分析和博客和其他文本流的分割","authors":"Yan Qi, Compo Sci, Eng Dept, K. Selçuk, Candan Sci Comp","doi":"10.1145/1149941.1149944","DOIUrl":null,"url":null,"abstract":"Weblogs (blogs) are becoming prominent forms of information exchange in the Internet. A large number and variety of blogs, like personal journals or commentaries, are available for general consumption. However, effective indexes and navigation structures (like the table of content in a book) are not available for blogs. Therefore, it is generally not possible to navigate among entries in a given collection of blog entries in an informed manner. This paper focuses on the segmentation of entries in filter-type [9] blogs, with the aim of using this information for developing hypertext and navigational helps. In particular, we are interested in the analysis of topic development patterns that can provide information about not only the entries themselves, but how these entries develop and relate to each other. The proposed algorithm, CUTS, maps entries into a curve in a way that makes apparent a variety of topic development patterns. We then use curve analysis for automatic segmentation of topics. The resulting base topic segments are classified into different topic development patterns that can be visualized and indexed. Experimental results show that the proposed technique has very good performance in identifying boundaries in text streams, especially filter style blogs, versus existing schemes. Furthermore, compared with other topic segmentation methods, the proposed mechanism highlights not only topic boundaries, but also topic development patterns.","PeriodicalId":134809,"journal":{"name":"UK Conference on Hypertext","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"41","resultStr":"{\"title\":\"CUTS: CUrvature-based development pattern analysis and segmentation for blogs and other Text Streams\",\"authors\":\"Yan Qi, Compo Sci, Eng Dept, K. Selçuk, Candan Sci Comp\",\"doi\":\"10.1145/1149941.1149944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Weblogs (blogs) are becoming prominent forms of information exchange in the Internet. A large number and variety of blogs, like personal journals or commentaries, are available for general consumption. However, effective indexes and navigation structures (like the table of content in a book) are not available for blogs. Therefore, it is generally not possible to navigate among entries in a given collection of blog entries in an informed manner. This paper focuses on the segmentation of entries in filter-type [9] blogs, with the aim of using this information for developing hypertext and navigational helps. In particular, we are interested in the analysis of topic development patterns that can provide information about not only the entries themselves, but how these entries develop and relate to each other. The proposed algorithm, CUTS, maps entries into a curve in a way that makes apparent a variety of topic development patterns. We then use curve analysis for automatic segmentation of topics. The resulting base topic segments are classified into different topic development patterns that can be visualized and indexed. Experimental results show that the proposed technique has very good performance in identifying boundaries in text streams, especially filter style blogs, versus existing schemes. Furthermore, compared with other topic segmentation methods, the proposed mechanism highlights not only topic boundaries, but also topic development patterns.\",\"PeriodicalId\":134809,\"journal\":{\"name\":\"UK Conference on Hypertext\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"41\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"UK Conference on Hypertext\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1149941.1149944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"UK Conference on Hypertext","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1149941.1149944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 41

摘要

网络日志(博客)正在成为互联网上重要的信息交换形式。大量的博客,如个人日志或评论,可供一般消费。然而,有效的索引和导航结构(如书中的目录)并不适用于博客。因此,通常不可能以明智的方式在给定的博客条目集合中的条目之间导航。本文主要研究过滤式[9]博客中条目的分割,目的是利用这些信息来开发超文本和导航帮助。特别是,我们对主题开发模式的分析感兴趣,这些模式不仅可以提供关于条目本身的信息,还可以提供关于这些条目如何开发和相互关联的信息。所提出的算法CUTS将条目映射到曲线中,从而使各种主题开发模式变得明显。然后,我们使用曲线分析对主题进行自动分割。得到的基本主题段被分类为不同的主题开发模式,这些模式可以可视化并建立索引。实验结果表明,与现有的算法相比,该算法在文本流边界识别方面具有很好的性能,特别是在过滤风格的博客中。此外,与其他主题分割方法相比,该方法不仅突出了主题边界,而且突出了主题发展模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CUTS: CUrvature-based development pattern analysis and segmentation for blogs and other Text Streams
Weblogs (blogs) are becoming prominent forms of information exchange in the Internet. A large number and variety of blogs, like personal journals or commentaries, are available for general consumption. However, effective indexes and navigation structures (like the table of content in a book) are not available for blogs. Therefore, it is generally not possible to navigate among entries in a given collection of blog entries in an informed manner. This paper focuses on the segmentation of entries in filter-type [9] blogs, with the aim of using this information for developing hypertext and navigational helps. In particular, we are interested in the analysis of topic development patterns that can provide information about not only the entries themselves, but how these entries develop and relate to each other. The proposed algorithm, CUTS, maps entries into a curve in a way that makes apparent a variety of topic development patterns. We then use curve analysis for automatic segmentation of topics. The resulting base topic segments are classified into different topic development patterns that can be visualized and indexed. Experimental results show that the proposed technique has very good performance in identifying boundaries in text streams, especially filter style blogs, versus existing schemes. Furthermore, compared with other topic segmentation methods, the proposed mechanism highlights not only topic boundaries, but also topic development patterns.
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:604180095
Book学术官方微信