Adaptive user profiling for deviating user interests

M. A. Zeb, M. Fasli
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引用次数: 9

Abstract

Although the World Wide Web has evolved to be an enormous source of information over the last decade, finding the required information poses a significant challenge to users as there is simply too much information available. Therefore systems that enable users to perform personalised information searches are becoming increasingly important. This paper presents a mechanism which provides recommendations based on a user profile that adapts to the changing interests of the user. Taking the multiple and diverse user interests into consideration, such as the short-term, long-term and periodic interests, the proposed mechanism constructs a user profile that evolves according to these interests. Articles from different news sources are presented to the users that they have subscribed to through an RSS aggregator and are ranked according to the user's profile. The mechanism adapts the user profile according to the changing user interests automatically and makes recommendations based on this profile.
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针对偏离用户兴趣的自适应用户分析
虽然在过去的十年中,万维网已经发展成为一个巨大的信息来源,但是要找到所需的信息对用户来说是一个巨大的挑战,因为可用的信息实在太多了。因此,使用户能够执行个性化信息搜索的系统变得越来越重要。本文提出了一种基于用户配置文件的推荐机制,该机制可以适应用户不断变化的兴趣。该机制考虑了用户兴趣的多样性,如短期兴趣、长期兴趣和周期性兴趣,构建了根据这些兴趣演变的用户画像。来自不同新闻来源的文章通过RSS聚合器呈现给用户,并根据用户的配置文件进行排名。该机制根据用户兴趣的变化自动调整用户配置文件,并根据该配置文件进行推荐。
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