Web personalization issues in big data and Semantic Web: challenges andopportunities

Web personalization is a process that utilizes a set of methods, techniques, and actions for adapting the linking structure of an information space or its content or both to user interaction preferences. The aim of personalization is to enhance the user experience by retrieving relevant resources and presenting them in a meaningful fashion. The advent of big data introduced new challenges that locate user modeling and personalization community in a new research setting. In this paper, we introduce the research challenges related to Web personalization analyzed in the context of big data and the Semantic Web. This paper also introduces some models and approaches that can bridge the gap between the two. Future challenges and opportunities related to Web personalization, analyzed from the big data and Semantic Web perspective, are also presented. The research challenges outlined in this paper involve the scrutability of user models in personalization, generic personalization, meta-personalization, open corpus personalization, and semantic data modeling.

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