1. Exploiting Preference Queries for Searching Learning Resources Fabian Abel, Eelco Herder, Philipp Kärger, Daniel Olmedilla, Wolf Siberski L3S Research Center, Hannover, Germany kaerger@L3S.de

2. “Exploiting Preference Queries for Searching Learning Resources ” 2EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Outline 1.What exactly is a preference? 2.A realistic search scenario 3.How preferences help 4.Prototypical implementation 5.Conclusions and future work

3. “Exploiting Preference Queries for Searching Learning Resources ” 3EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de First, let’s clarify: What exactly is a Preference ?

4. “Exploiting Preference Queries for Searching Learning Resources ” 4EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de –A preference is more than just one preferred value of an attribute Simple: “I like green and English” Main assumption: –A preference is an order of values Better: “I prefer green to red and my last option is brown. I prefer English but German is also fine.”

5. “Exploiting Preference Queries for Searching Learning Resources ” 5EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de “How can this help for technology enhanced learning?”

6. “Exploiting Preference Queries for Searching Learning Resources ” 6EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Basic example: 1.“I prefer a cheap course to an expensive one.” 2.“I prefer to have only a few other participants sharing my course instead of an overcrowded course.”

7. “Exploiting Preference Queries for Searching Learning Resources ” 7EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de participants price 5 10 15 1 1020 30 40 20

8. “Exploiting Preference Queries for Searching Learning Resources ” 8EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Beyond price and number of participants, learners may have lots of preferences: Language an object is presented in Where and when does education happen By which means (e.g., at a computer or in a reading) Who is teaching/authoring Type of examination/assessment Type of interactivity Text or picture-oriented …

9. “Exploiting Preference Queries for Searching Learning Resources ” 9EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de 2. A realistic search scenario

10. “Exploiting Preference Queries for Searching Learning Resources ” 10EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de

11. “Exploiting Preference Queries for Searching Learning Resources ” 11EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de v current search approaches: –conjunctive querying: search for an object bearing all the most preferred attributes –best alternatives act as hard constraints –“return all courses which are on Wednesday AND take 3 months AND with no cost AND …”  in most of the cases no result

12. “Exploiting Preference Queries for Searching Learning Resources ” 12EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de v current search approaches: –disjunctive querying: search for an object bearing one of all the given properties –e.g., return courses which take 2 months OR 3 months OR 4 months OR are on Wednesday OR on Monday OR …  will return almost all objects as result

13. “Exploiting Preference Queries for Searching Learning Resources ” 13EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de preference solution:  we can make use of the given alternatives for each dimension (e.g., if Wednesday is not possible, I go for Monday)  but which courses are optimal according to the preferences?

14. “Exploiting Preference Queries for Searching Learning Resources ” 14EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de 3. How preferences help finding the desired course

15. “Exploiting Preference Queries for Searching Learning Resources ” 15EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de The desired courses are Pareto optimal: A course is optimal if no other course is better (or equal) in all preference dimensions. example: if a course has the same price but more participants than another, it is not optimal. I.e., the first course is pareto-dominated by the second one

16. “Exploiting Preference Queries for Searching Learning Resources ” 16EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de No result bears optimal conditions! CourseWeekdayPriceDistanceLocation ASunday44 Euro2 kmsouth BFriday44 Euro2 kmsouth CSaturday72 Euro2 kmsouth DSaturdayno cost10 kmnorth ESaturday72 Euro10 kmnorth

17. “Exploiting Preference Queries for Searching Learning Resources ” 17EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de 4. Prototypical Implementation

18. “Exploiting Preference Queries for Searching Learning Resources ” 18EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de test data set: 10,000 lectures held at University Hannover query language: a novel preference extension of the RDF query language SPARQL realized as Web Service integrated in the Personal Reader Framework

19. “Exploiting Preference Queries for Searching Learning Resources ” 19EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de User Interface

20. “Exploiting Preference Queries for Searching Learning Resources ” 20EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de

21. “Exploiting Preference Queries for Searching Learning Resources ” 21EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Promising result: the query: Return courses about mathematics. I am interested in readings rather than in tutorials and seminars. If possible, I would like to attend a 90 minutes lecture. 60 minutes are also fine, but 120 minutes are too long. I like to have the lecture in the morning rather than in the afternoon. Due to the lunch break, noon is not possible for me. I don't want to have a lecture on Friday. Thursday would be my first choice, then Tuesday. Wednesday would also be acceptable and is preferred to Monday, where I am usually still at my parents.

22. “Exploiting Preference Queries for Searching Learning Resources ” 22EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de 5. Conclusions and Future Work

23. “Exploiting Preference Queries for Searching Learning Resources ” 23EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Conclusions: –Classical search mechanisms consider “preferences” as hard constraints Problem if no optimal solution exists –Preference-based queries allow for soft constraining the results pruning the non dominated learning resources dramatically decreases the size of the result set

24. “Exploiting Preference Queries for Searching Learning Resources ” 24EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Observation: –Users do not need to specify all preferences Only those they want –Preferences might be automatically extracted If the student’s schedule is full on Monday then … If the student’s results are bad for oral exams then … –Default preferences might be turned on Cheapest price, with certification, lowest distance, highest reputation, etc…

25. “Exploiting Preference Queries for Searching Learning Resources ” 25EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Future Work –extend preference based search with preference based recommendation –combine this with established collaborative filtering strategies hybrid solution (e.g., to solve cold start problems) –using preferences in Curriculum planning

26. “Exploiting Preference Queries for Searching Learning Resources ” 26EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de semweb.kbs.uni-hannover.de:8081 /PreferenceQueryGUI/

27. “Exploiting Preference Queries for Searching Learning Resources ” 27EC-TEL, September 2007Philipp Kärger - kaerger@L3S.de Thanks for your attention. Philipp Kärger L3S Research Center Hannover, Germany kaerger@L3S.de