An architecture for privacy-enabled user profile portability on the web of data

HetRec '10 Pub Date : 2010-09-26 DOI:10.1145/1869446.1869449
B. Heitmann, J. G. B. Kim, Alexandre Passant, Conor Hayes, H. Kim
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引用次数: 30

Abstract

Providing relevant recommendations requires access to user profile data. Current social networking ecosystems allow third party services to request user authorisation for accessing profile data, thus enabling cross-domain recommendation. However these ecosystems create user lock-in and social networking data silos, as the profile data is neither portable nor interoperable. We argue that innovations in reconciling heterogeneous data sources must be also be matched by innovations in architecture design and recommender methodology. We present and qualitatively evaluate an architecture for privacy-enabled user profile portability, which is based on technologies from the emerging Web of Data (FOAF, WebIDs and the Web Access Control vocabulary). The proposed architecture enables the creation of a universal "private by default" ecosystem with interoperability of user profile data. The privacy of the user is protected by allowing multiple data providers to host their part of the user profile. This provides an incentive for more users to make profile data from different domains available for recommendations.
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一种在数据网络上支持隐私的用户配置文件可移植性的体系结构
提供相关建议需要访问用户配置文件数据。当前的社交网络生态系统允许第三方服务请求用户授权访问个人资料数据,从而实现跨域推荐。然而,这些生态系统造成了用户锁定和社交网络数据孤岛,因为个人资料数据既不可移植也不可互操作。我们认为,协调异构数据源的创新也必须与架构设计和推荐方法的创新相匹配。我们提出并定性地评估了一种基于新兴的数据网络(FOAF、webid和Web访问控制词汇表)技术的支持隐私的用户配置文件可移植性的体系结构。所提出的体系结构支持创建具有用户配置文件数据互操作性的通用“默认私有”生态系统。通过允许多个数据提供者托管其用户配置文件的一部分,可以保护用户的隐私。这将激励更多的用户将来自不同领域的配置文件数据用于推荐。
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