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ExploitingPreference Queries for
Searching Learning Resources
Fabian Abel, Eelco Herder, Philipp Kärger, Daniel Olmedilla,
Wolf Siberski
L3S Research Center, Hannover, Germany
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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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First, let’s clarify:
What exactly is a
Preference ?
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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.”
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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“How can this
help for
technology enhanced learning?”
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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.”
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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part
icip
ants
price
5
10
15
110
20
30
40
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EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
• …
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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2.A realistic search scenario
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
12
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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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?
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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3.How preferences help
finding the desired course
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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4.
Prototypical Implementation
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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User Interface
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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5.Conclusions and Future Work
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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…
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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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
EC-TEL, September 2007 Philipp Kärger - [email protected]
“ ExploitingPreference Queries forSearching Learning Resources ”
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Thanks for your attention.
Philipp Kärger
L3S Research Center
Hannover, Germany