使用公开可用的网络文档生成个性化摘要

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Pub Date : 2008-12-09 DOI:10.1109/WIIAT.2008.332

Chandan Kumar, Prasad Pingali, Vasudeva Varma

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引用次数: 19

摘要

许多知识工作者越来越多地使用在线资源来查找他们的专业和感兴趣的文章的最新发展。为了从这样的多个在线信息源中提取相关信息，采用了摘要的方法。当前的摘要系统为所有用户生成统一版本的摘要。然而，一般性质的摘要不符合用户的背景和兴趣。在本文中，我们建议使摘要过程针对用户，并提出了一种针对每个人的兴趣定制的在线文章的个性化摘要的设计。Web上可用的用户数据用于建模他们的背景和兴趣。对科技领域的新闻文章进行了一项受控的以用户为中心的定性评价，结果表明个性化摘要的用户满意度高于通用摘要。

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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Generating Personalized Summaries Using Publicly Available Web Documents

Many knowledge workers are increasingly using online resources to find out latest developments in their specialty and articles of interest. To extract relevant information from such multiple online information sources summarization is being used. Current summarization systems produce a uniform version of summary for all users. However summaries which are generic in nature do not cater to the userpsilas background and interests. In this paper we propose to make the summarization process user specific and present a design for generating personalized summaries of online articles that are tailored to each personpsilas interest. The userpsilas data available on Web is used for model their background and interest. A controlled user-centered qualitative evaluation carried out on news articles of science and technology domain, indicates better user satisfaction with personalized summaries compared to generic summaries.

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来源期刊

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology

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