GeniUS is a topic and user modeling library that produces semantically meaningful user profiles from social web data to enhance interoperability between applications. It aggregates relevant user information from sources like Twitter, enriches it with semantic data, and generates customized profiles according to application needs. Evaluation shows domain-specific profiles generated by GeniUS improve recommendation performance compared to generic profiles, with performance varying slightly between domains.

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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