Personalizing the Digital Library Experience

1. Personalizing the Digital Library Experience Nicholas J. Belkin, Jacek Gwizdka, Xiangmin ZhangSCILS, Rutgers University nick@belkin.rutgers.eduhttp://scils.rutgers.edu/imls/poodle

2. Goals of Personalization • 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

3. Types of Personalization • With respect to predictions of usefulness/ relevance of items, e.g. • modify query • re-rank results • With respect to interaction, e.g. • different interface designs for different tasks • different interface designs for different individuals

4. Facets of Personalization • Viewing/saving/evaluating behaviors • Task • Problem state • Personal characteristics • Personal preferences • Context/situation

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

6. 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)

7. 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

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

9. 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

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

11. 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

12. Evidence for Personalization • Explicit evidence, e.g. • Relevance judgments • Statements of goals, problems, etc. • Location; time of day, week, month, year • Implicit evidence, e.g. • Dwell time • Clickthrough • Past searches, uses • Concurrent activities

13. Interpreting Implicit Evidence • Dwell time is evidence of usefulness / relevance / interestingness • But needs to be interpreted in terms of task (Kelly, 2004; White & Kelly, 2006) • Is dependent on individual characteristics (Kelly, 2004) • In general, evidence from any one facet could affect interpretation of evidence from any other facet • All evidence is probably individual-dependent

14. Our Approach • Investigate in depth aspects of specific facets, e.g. • Task • Domain knowledge • Cognitive characteristics • Investigate the interactions among the different facets • Implement and test within an integrative system framework • Using a client-side “personalization assistant”

15. Initial Investigation • Three months of logs of all computer use and searching behavior for each of seven Ph.D. students • Judgments, by subjects, of usefulness of pages viewed as results of searching, with task type, duration and stage of task, topic, and familiarity with topic • Both from Kelly (2004).

16. Data Analysis • Exploratory analysis of relationships among dwell time and each of: task and topic familiarity; task stage; and, task duration, to determine most accurate dwell time value for predicting usefulness • Exploratory analysis of current and past behavior as indicator of task type, task stage, and task/topic familiarity

17. Results to Date for Task Stage

18. Results to Date for Task Type

19. Results to Date for Topic Familiarity • The three-way interaction of individual*usefulness*topic familiarity was significant, meaning that considering both the individual and topic familiarity information may be helpful in predicting usefulness by display time.

20. Next Steps • Begin three concurrent investigations of • Domain knowledge • Task • Cognitive characteristics • Each investigation to consider one additional facet • Each to identify: • Evidence for particular facet • Use of evidence for personalization • Interaction of main facet with one other

21. Then … • Implement results from previous investigations in prototype system • Experiments to test methods of identification of evidence, and the use of that evidence from all facets simultaneously

22. And Finally • Move from experimental prototype to robust client-side personalization assistant • Distribute assistant to subjects in a real work environment • Compare performance, usability, acceptability, etc. between those with, and those without the personalization assistant • Make the personalization assistant available as open source software