1. GeniUS: Generic User Modeling Library
for the Social Semantic Web
JIST2011, December 2011, Hangzhou, China
QiGao, Fabian Abel, Geert-Jan Houben
{q.gao, f.abel, g.j.p.m.houben}@tudelft.nl
Web Information Systems
Delft University of Technology
Delft
University of
Technology

2. What we do: Science and Engineering for the
Personal Web
domains: news social mediacultural heritage public datae-learning
Personalized Personalized
Adaptive Systems
Recommendations Search
Analysis and
User Modeling
Semantic Enrichment,
Linkage and Alignment
user/usage data
Social Web
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 2

3. Motivation
• Sparsity problem
Product • do not have enough useful
Recommender information for a (new) user
? ? • Possible solution: gatheringuser data from
other sources
• But not all data may be relevant for
User Modeling
the given application context.
• how to filter out user data that does
not fit the target application context?
I’m a new user.
Recommend me
some product
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 3

4. Research Challenges of GeniUS
Various applications in different domains
Product Movie Hotel Product
recommender recommender recommender recommender
Profile
?
customized user
profile construction
Analysis and interested in:
User Modeling
Product Movie location
Semantic Enrichment
How can we build a flexible and extensible
user modeling functionality that adapts to
the demands of a given application context?
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 4

5. What is GeniUS?
• GeniUSis a topic and user modeling software library that
• produces semantically meaningful profiles to enhance the
interoperability of profiles between applications;
• provides functionality for aggregating relevant information about a
user from the Social Web;
• generates domain-specific user profiles according to the information
needs of different applications;
• is flexible and extensible to serve different applications.
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 5

6. GeniUS: Generic Topic and User Modeling Library
for the Social Semantic Web
Semantic Web
semantic data
Filter
enriched
user data items user profiles RDF
Item items Enrichmen Weighting
Serializatio
Fetcher t Function interested in:
n
product location
Social Web
Modeling RDF
Configuration Repository
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 6

7. Item
Fetcher
GeniUS modules: Item Fetcher and Semantic Enrichment
Enrichmen
t
raw content
a <sioc:Post> ; sioc:has_topicdbpedia:Apple_Inc;
Twitter SpotLight,
dcterms:created … ; sioc:has_topicdbpedia:GarageBand;
API Zemanta,
sioc:has_creator …; sioc:has_topicdbpedia:Ipad;
OpenCalais
sioc:content … .
Social Web
Awesome, love the new
Awesome, love the new Garageband for iPad #apple
GaragebandiPad#apple
Garageband for iPad #apple
dbpedia:GarageBand dbpedia:Ipad dbpedia:Apple_Inc
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 7

8. Weighting
GeniUS modules: Weighting Function and Function
RDF Serialization RDF
Serializatio
n
weight(dbpedia:Garag
eBand)
weight(dbpedi
a:Jazz)
weight(dbpedia:Secon
TF d_Life)
RDF
TF-IDF
Serialization
Time-sensitive
the weighted
interests vocabulary
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 8

9. Filter
GeniUS modules: Configuration and Filter Modeling
Configuration
(Jazz, 0.5889)
(Second_Life,
0.4101)
(Second_Life,
0.3114) SELECT DISTINCT ?t WHERE {
Filter
? <rdf:type><dbpedia-owl:Software> } (GarageBand,
(GarageBand, 0.2158)
0.1638)
enriched
items items
Twitter
SpotLight TF
API
Modeling
Configuration
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 9

10. GeniUS: Generic Topic and User Modeling Library
for the Social Semantic Web
Semantic Web
GeniUS User Profile Applications
interested in:
product location …
Social Web
How do user profiles generated by GeniUS support
different types of applications?
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 10

11. Analysis of Domain-specific User Profile Construction
• Dataset
• 72 Twitter users (CS researchers) observed over a period of 6 months
(>40,000 tweets)
• a variety of topics mentioned in the tweets
• Research questions
• 1. What are the characteristics of (complete) Twitter-based profiles
generated with GeniUS ?
• 2. Can domain-specific profiles be derived from Twitter activities ?
• 3. What are the characteristics of such domain-specific profiles?
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 11

12. Analysis of Domain-specific User Profile Construction
average number of entities: 1097.1
average number of types: 35.0
a potential to generate domain-specific profiles
by categorizing entities according to their types
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 12

13. Analysis of Domain-specific User Profile Construction
domain: location the more specific the domain
generic
domain: entertainment the smaller the profiles
(all domains)
× domain: product
Are the domain-specific user profiles beneficial for
supporting different recommendation applications?
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 13

14. Evaluation of Domain-specific User Profile Construction
• Task: Recommending domain-specific tweets
• Domains:
• three domains: location, entertainment, product
• three sub-domains of product: book, software, music
• Recommender algorithm: cosine similarity between profile
and candidate item
• Ground truth: relevant (re-)tweets of users
• Candidate items: all the tweets posted during evaluation
period Recommendations = ?
P(u)= ? user profile
time
1 month
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 14

15. Evaluation results
the domain-specific user modeling strategies
improve the performance of recommendations
three different domains
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 15

16. Evaluation results
The sub-domain-specific user modeling strategy
also improve the performance of recommendation.
three sub-domains
of product
The user modeling quality varies only slightly
between the different domains
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 16

17. Wrap up
• GeniUS: Generic topic and User modeling library for the Social Semantic Web
• exploits traces (e.g. tweets) that people leave on the Social Web
• enriches the semantics of these traces
• constructs semantic user profiles
 profile construction can be customized and is adapted to a given application context
• Analysis:
• Twitter-based user profiles contain a great variety of topics
• GeniUS succeeds in generating profiles for different applications and domains
• Evaluation:
• domain-specific user modeling strategies (powered by the semantic filtering of
GeniUS) allow clearly for the best performance
• the more GeniUS adapts to the given domain (and application context) the better
the performance
GeniUS: Generic User ModelingLibraryfor the SocialSemantic Web 17

18. Thank You!
q.gao@tudelft.nl
Twitter: @qigaosh
QiGao
http://wis.ewi.tudelft.nl/tweetum/
http://wis.ewi.tudelft.nl/genius/
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