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Getting Personal: Personalization of Support for Interaction with Information

Getting Personal: Personalization of Support for Interaction with Information. Nicholas J. Belkin Department of Library and Information Science School of Communication, Information & Library Studies Rutgers University belkin@rutgers.edu. Adaptation and Personalization.

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Getting Personal: Personalization of Support for Interaction with Information

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  1. Getting Personal: Personalization of Support for Interaction with Information Nicholas J. BelkinDepartment of Library and Information ScienceSchool of Communication, Information & Library StudiesRutgers Universitybelkin@rutgers.edu

  2. Adaptation and Personalization • Personalization of IR is a subset of Adaptive IR • Adaptive IR may include adaptation of system features based on non-user factors • Personalization of IR is explicitly concerned with user-based factors • Personalization may be the more interesting, more difficult, and more fruitful approach

  3. Personalization: What’s the Goal? • To make the user’s interaction with information as effective and pleasurable as possible • To tailor the user’s interaction with information to the user’s characteristics, preferences, the specific circumstances of the interaction, and the user’s goals

  4. Implication of Personalization • Systems are tailored to individuals (or groups) • Inherent contradiction between goals of effective access for all, and effective access for one, or a few • Resolution of this contradiction is a major problem for the personalization agenda

  5. Personalization: The (Modeling) Past • Taylor and the reference interview • Dervin and sense-making • Belkin; Belkin, Oddy & Brooks, ASK • Wersig, et al., MONSTRAT • Croft & Thompson, I3R • Vickery & Brooks, PLEXUS • Distributed Expert-Based Information Systems

  6. Personalization: The Problems with the (Modeling) Past • Eliciting the information needed for the models • Models are (relatively) static • Models are inherently uncertain • Interaction is not an intrinsic property of the modeling agenda

  7. Personalization: The (Interactive) Past • Studying the interaction between user of system, and intermediary • Taylor; Ingwersen; Belkin, Oddy & Brooks; Belkin, Seeger & Wersig • Problems with this approach: Functionality may be correct, but ignores direct interaction with information • Nordlie addressed this problem to some extent

  8. Personalization: The Present • Depends upon group, as well as individual, behavior • Based primarily on evidence from past and current interactions • Studies (systems) typically address only one facet of personalization

  9. Facets of Personalization • Relevance/usefulness/interest • Task • Problem state • Personal characteristics • Personal preferences • Context/situation

  10. Relevance, etc. • Implicit evidence (Kelly & Teevan) • Time on “page” • Click-through • Previous uses • Others like the interactant • Explicit evidence • Relevance feedback (of various sorts)

  11. Task • “Everyday” or “leading” or “work” task • Complexity, difficulty, “type” (Bystrom, et al.) • Information seeking task • Choice of strategies, sources (Bates, Pejtersen, berrypicking) • Information searching task • Moves, shifts (Bates; Xie)

  12. Problem State • What has been done before • Previous searches • Stage in the Problem Solving Process (Kuhlthau; Vakkari) • What is being done now • Immediately past behavior in searching, other concurrent activities

  13. Personal Characteristics • Knowledge • of topic, of task • Demography • gender, age • Individual differences • Cognitive abilities • Affect

  14. Personal Preferences • For types of interaction • Mixed or single initiative • For styles of interaction • Display, navigation • For support for interaction • Active, passive • Integrated, separate • For types of information • Genre, level

  15. Context, Situation • Location • Physical environment • Mobile, static • Salience • Urgency • Time • of day, of week, of month, of season, … • Other interactants • Group conditions • Social norms

  16. Overall Goals for Personalization • Determining significant aspects of each facet • Determining means for identifying these aspects • Determining means for implementation of support • Integrating all facets of personalization into single system frameworks

  17. Progress toward these Goals • A good number of studies of single facets • Some evidence for significance of different aspects of facets • Some work on identifying significant aspects • Some work on implementing understanding of aspects in system support • Only a very few studies on integrating several facets of personalization

  18. The Future • Personalization of support for interaction with information is clearly the next significant step for achieving effective and pleasurable interaction • There is much to be done, with great opportunities for research • The type of research which needs to be done is extremely difficult, and therefore likely to be a lot of fun • This workshop will help put us on the right paths

  19. Thanks • To Colleen Cool, Gheorghe Muresan • To PhD students Jeonghyun Kim, Yuelin Li, Xiaojun Yuan • To the members, students and faculty, of the Rutgers Information Interaction Laboratory

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