Aggregated, interoperable and multi-domain user profiles for the social web
Aggregated, interoperable and multi-domain user profiles for the social web
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DOI：
10.1145/2362499.2362506
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发表时间：
2012-09
期刊：
影响因子：
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通讯作者：
F. Orlandi;J. Breslin;Alexandre Passant
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文献类型：
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作者：
F. Orlandi;J. Breslin;Alexandre Passant
用户分析技术主要集中在检索和表示用户的知识，上下文和兴趣，以提供建议，个性化搜索，并建立用户自适应系统。然而，在单个社交网络上构建用户配置文件限制了配置文件的质量和完整性，特别是当配置文件的互操作性是关键并且其在不同网站上的重用对于提供其他类型的个性化是必要的时。事实上，最近的研究表明，社交网络上的用户经常使用不同的社交网站，有时不重叠，目的和兴趣。在本文中，我们描述了我们的方法，自动创建和聚合的互操作性和多域用户配置文件的利益，使用语义技术。此外，我们提出了一个用户研究不同的用户分析技术的社交网站，特别是Twitter和Facebook。在这方面，我们的用户评估的结果的基础上，我们调查（i）不同的方法的准确性分析，（ii）时间衰减函数对排名用户兴趣的影响，以及（iii）合并不同的用户模型使用语义技术的好处。
User profiling techniques have mostly focused on retrieving and representing a user's knowledge, context and interests in order to provide recommendations, personalise search, and build user-adaptive systems. However, building a user profile on a single social network limits the quality and completeness of the profile, especially when interoperability of the profile is key and its reuse on different sites is necessary for providing other types of personalisation. Indeed recent studies have shown that users on the Social Web often use different social networking sites for diverse, and sometimes non-overlapping, purposes and interests. In this paper, we describe our methodology for the automatic creation and aggregation of interoperable and multi-domain user profiles of interests using semantic technologies. Moreover, we propose a user study on different user profiling techniques for social networking websites in general, and for Twitter and Facebook in particular. In this regard, based on the results of our user evaluation, we investigate (i) the accuracy of different methodologies for profiling, (ii) the effect of time decay functions on ranking user interests, and (iii) the benefits of merging different user models using semantic technologies.