Foxinfo1.0: A Chinese Topic-Oriented Search Engine

Ke Sun, Lei Lin, Bingquan Liu, Chengjie Sun, Xiaolong Wang
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Abstract

Topic-oriented search engine (topic-search) is a new IR service which provides compounded types of information with certain user queried topic in one page. It firstly categorizes user query into a certain domain, and then organizes several types of information based on the query keywords into a magazine-style topic page for user. In this paper, we propose a Chinese topic-oriented search engine service, named as Foxinfo1.0, which provides a 360 degree view of the topic that interests the users who're seeking it. Different from the original topic-search which employs the keyword-based topic to retrieve and aggregate relevant information, Foxinfo1.0 could organize information from different abstraction level by employing tag to describe the topics of queries and information. Further, in order to predict tags from queries and web documents, a tag prediction algorithm named as CTAG is proposed, which could concern tags from different levels, and performs much better than the baseline method like AutoTag.
Foxinfo1.0:中文主题搜索引擎
面向主题的搜索引擎(topic-search)是一种新的IR服务,它在一个页面上提供具有特定用户查询主题的复合类型的信息。它首先将用户查询分类到某个领域,然后根据查询关键字将几种类型的信息组织成杂志式的主题页面供用户使用。在本文中,我们提出了一个中文主题搜索引擎服务,命名为Foxinfo1.0,它提供了一个360度的主题视图,感兴趣的用户正在寻找它。与原来的主题搜索采用基于关键词的主题来检索和聚合相关信息不同,Foxinfo1.0可以通过使用标签来描述查询和信息的主题,从不同的抽象层次来组织信息。此外,为了从查询和web文档中预测标签,提出了一种名为CTAG的标签预测算法,该算法可以关注不同层次的标签,并且性能比AutoTag等基准方法要好得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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