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School of something FACULTY OF OTHER School of Computing FACULTY OF ENGINEERING Web Search Personalization via Social Bookmarking and Tagging COMP3740.

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Presentation on theme: "School of something FACULTY OF OTHER School of Computing FACULTY OF ENGINEERING Web Search Personalization via Social Bookmarking and Tagging COMP3740."— Presentation transcript:

1 School of something FACULTY OF OTHER School of Computing FACULTY OF ENGINEERING Web Search Personalization via Social Bookmarking and Tagging COMP3740 CR32 Knowledge Management and Adaptive Systems Lecturers: Eric Atwell and Vania Dimitrova

2 Michael Noll, University of Potsdam We will watch a VideoLectures.net video: Michael NollMichael Noll, University of Potsdam Web Search Personalization via Social Bookmarking and Tagging (27 minutes) This introduces topics to be covered in Semester 2: On completion of this module, students should be able to Apply appropriate techniques to identify user needs, analyse requirements, design, implement and evaluate user-adaptive systems; Describe specified personalisation techniques and apply at least one to a practical problem; Understand the potential for and drawbacks of personalisation

3 Summary In this talk, we present a new approach to web search personalization based on user collaboration and sharing of information about web documents. The proposed personalization technique separates data collection and user profiling from the information system whose contents and indexed documents are being searched for, i.e. the search engines, and uses social bookmarking and tagging to re-rank web search results. It is independent of the search engine being used, so users are free to choose the one they prefer, even if their favorite search engine does not natively support personalization. We show how to design and implement such a system in practice and investigate its feasibility and usefulness with large sets of real-word data and a user study.

4 Web Search Personalization

5 Syllabus for Semester 2 User Diversity and Personalisation: Properties of the user modelled; Data about the user collected; Personalisation techniques (e.g. customisation, stereotypes, collaborative filtering and recommendations). Application of adaptive techniques: personalisation for e-commerce, adaptive user interfaces, adaptive support for decision making and group work, individualised e-learning, personalised ubiquitous computing. HCI and user adaptive systems: identifying user needs and obtaining requirements for personalised systems; involving users in design; incremental prototyping; evaluation.Potential for and drawbacks of personalisation and privacy.


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