KANSHIN:使用多语言博客文章的跨语言关注分析系统

T. Fukuhara, A. Kimura, Y. Arai, Takayuki Yoshinaka, H. Masuda, T. Utsuro, Hiroshi Nakagawa
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引用次数: 5

摘要

介绍了一种基于多语言博客文章的跨语言关注分析体系结构及其原型系统。随着生活在不同国家的不同人群使用Web,跨语言信息检索(CLIR)在下一代搜索中扮演着重要的角色。在本文中,我们提出了一个CLCA作为CLIR应用程序之一,以方便用户跨语言查找人们的关注点。提出了一种CLCA的分层架构,并提出了原型系统KANSHIN。该系统收集日语、中文、韩语和英语的博客文章,并分析不同语言的关注点。用户可以从时间、地理和博客站点网络等多个角度找到关注点。该系统还方便用户使用维基百科浏览多语言关键词,并方便用户查找垃圾博客。描述了CLCA体系结构和系统的概述。
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KANSHIN: A Cross-Lingual Concern Analysis System Using Multilingual Blog Articles
An architecture of cross-lingual concern analysis (CLCA) using multilingual blog articles, and its prototype system are described. As various people who are living in various countries use the Web, cross-lingual information retrieval (CLIR) plays an important role in the next generation search. In this paper, we propose a CLCA as one of CLIR applications for facilitating users to find concerns of people across languages. We propose a layer architecture of CLCA, and its prototype system called KANSHIN. The system collects Japanese, Chinese, Korean, and English blog articles, and analyzes concerns across languages. Users can find concerns from several viewpoints such as temporal, geographical, and a network of blog sites. The system also facilitates users to browse multilingual keywords using Wikipedia, and the system facilitates users to find spam blogs. An overview of the CLCA architecture and the system are described.
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