Personalisation in the wild: providing personalisation across semantic, social and open-web resources

  • Authors:
  • Ben Steichen;Alexander O'Connor;Vincent Wade

  • Affiliations:
  • Trinity College Dublin, Dublin, Ireland;Trinity College Dublin, Dublin, Ireland;Trinity College Dublin, Dublin, Ireland

  • Venue:
  • Proceedings of the 22nd ACM conference on Hypertext and hypermedia
  • Year:
  • 2011

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Abstract

One of the key motivating factors for information providers to use personalization is to maximise the benefit to the user in accessing their content. However, traditionally such systems have focussed on mainly corporate or professionally authored content and have not been able to leverage the benefits of other material already on the web, written about that subject by other authors. Such information includes open-web information as well as user-generated content such as forums, blogs, tags, etc. By providing personalized compositions and presentations across these heterogeneous information sources, a potentially richer user experience can be created, leveraging the mutual benefits of professionally authored content as well as open-web information and active user communities. This paper presents novel techniques and architectures that extend the personalization reserved for corporate or professionally developed content with that of user generated content and pages in the wild. Complementary affordances of Personalized Information Retrieval and Adaptive Hypermedia are leveraged in order to provide Adaptive Retrieval and Composition of Heterogeneous INformation sources for personalized hypertext Generation (ARCHING). The approach enables adaptive selection and navigation according to multiple adaptation dimensions and across a variety of heterogeneous data sources. The architectures have been applied in a real-life personalized customer care scenario and a user study evaluation involving authentic information needs has been conducted. The evidence clearly shows that the system successfully blends a user's search experience with adaptive selection and navigation techniques and that the user experience is improved in terms of both task assistance and user satisfaction.