exploiting preference queries for searching learning resources fabian abel, eelco herder, philipp...

ExploitingPreference Queries for

Searching Learning Resources

Fabian Abel, Eelco Herder, Philipp Kärger, Daniel Olmedilla,

Wolf Siberski

L3S Research Center, Hannover, Germany

[email protected]

EC-TEL, September 2007 Philipp Kärger - [email protected]

“ ExploitingPreference Queries forSearching Learning Resources ”

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Outline

1. What exactly is a preference?

2. A realistic search scenario

3. How preferences help

4. Prototypical implementation

5. Conclusions and future work



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First, let’s clarify:

What exactly is a

Preference ?



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– 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.”



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“How can this

help for

technology enhanced learning?”



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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.”



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part

icip

ants

price

5

10

15

110

20

30

40

20



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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

• …



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2.A realistic search scenario



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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 monthsAND with no cost AND …”

in most of the cases no result



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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



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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?



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3.How preferences help

finding the desired course



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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



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No result bears optimal conditions!

Course Weekday Price Distance Location

A Sunday 44 Euro 2 km south

B Friday 44 Euro 2 km south

C Saturday 72 Euro 2 km south

D Saturday no cost 10 km north

E Saturday 72 Euro 10 km north



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4.

Prototypical Implementation



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• 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



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User Interface



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5.Conclusions and Future Work



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• 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



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• 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…



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• Future Work

– extend preference based search withpreference based recommendation

– combine this with established collaborative filtering strategies

• hybrid solution (e.g., to solve cold start problems)

– using preferences in Curriculum planning



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Thanks for your attention.

Philipp Kärger

L3S Research Center

Hannover, Germany

[email protected]

exploiting preference queries for searching learning resources fabian abel, eelco herder, philipp...

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