Presentation at Kno.e.sis - Feb 2012. The presentation describe my current PhD research at DERI and the work done in 5 weeks during a collaboration in Kno.e.sis with Pavan Kapanipathi, Prof. Amit Sheth, Prof. T. K. Prasad and the rest of the group. - video: http://youtu.be/MmF5HxIVUwA

1. User Profiling on the Social
Semantic Web
Fabrizio Orlandi, DERI (NUI Galway, Ireland)
Kno.e.sis – WSU Dayton, OH – 9 Feb 2012

2. User Profiling
“A user profile is a representation of information about an individual user
that is essential for the (intelligent) application we are considering” [1]
Contents of user profiles:
 user interests;
 the user’s knowledge, background and skills;
 user behavior;
 the user’s interaction preferences;
 the user’s individual characteristics;
 and the user’s context.
[1] S. Schiaffino, A. Amandi. 2009.

3. Research Questions
• How to collect and interlink user information from social media
websites to build enhanced and comprehensive user profiles?
• How to manage and merge user models from different
applications and social sites in an interoperable way?
• How to leverage provenance information and trust measures on
the Web of Data to improve Web personalisation?

4. Challenges – 1
• Information on the Social Web is stored in isolated data silos on
heterogeneous and disconnected social media websites
http://www.w3.org

5. Challenges – 2
• The Web of Data: a continuously evolving “open corpus”
LOD Cloud by R. Cyganiak and
A. Jentzsch

6. Challenges – 3
• Lack of provenance on the Web of Data: datasets on the Social Web
are often the result of data mashups or collaborative user activities

7. Challenges – 4
• User profiles should be represented in an interoperable way in order
to exchange information across different user adaptive systems
[U. Bojārs, A. Passant, J. Breslin]

8. Outline
1 3
2
The user profiling data process:
1. from user activities on heterogeneous social media websites,
2. to their provenance representation,
3. to the data aggregation and analysis

9. So far…
 State of the art analysis
 Modelling the structure of wikis
 Enabling semantic search on heterogeneous wiki systems
 Provenance of data in wikis
 Representation and extraction of provenance in Wikipedia and DBpedia
 Privacy Aware and Faceted User-Profile Management
 Personalized Filtering of the Twitter Stream…

10. Semantic Personalization of Social
Web Streams

11. Motivation
Twitter – Growth
Information Overload
11
http://www.cmswire.com/cms/customer-experience/35-key-twitter-statistics-infographic-012384.php

15. Motivation
• How many people should I follow?
• Am I receiving latest/complete information?
• How can I quickly tell the system what are my interests?

16. Approach -- Overview
The new
iPhone has a Broadcast
3.5-inch screen,
released today Football
User
Profiles
Filter
Apple

17. Annotate: iPhone Get
?user foaf:interest Subscribers
The new dbPedia:iPhone based on
iPhone has a 3.5- Union preference
inch screen, ?user foaf:interest
released today Category:Apple
Get Interested
Subscribers
Semantic Filter RDF
Notify Update
A
N RDF
N
O
Store and
Query Topics
Semantic
T
A
T
Fetch Updates Hub
O RSS Store FOAF
R
Update RSS
Profile Generator
Push Updates
to Interested
Users
Create Profile

18. User Profiling
Interlink social websites
Integration
& Merge and model user data
User Modelling
User Profile
Personalise users’ experience
using their profile
Recommendations Adaptive Systems
Search Personalisation

19. User Profiling

20. Profile Generator
• Data Extraction
– Twitter, Facebook
– Example: Tweets, FB Likes, posts, videos, etc.
• Profile Generation
– Interests extracted from collected data
• Entity spotting (user generated data)
• Explicit interests specified by user (Facebook likes etc.)
– Weighted Interests w/ DBpedia resources/categories
– FOAF profile

21. Semantic Filter
Get Interested Subscribers
RDF
Semantic Filter Notify Update
A
N
N
O
Store and
Query Topics
RDF
Semantic
T
A
T
Fetch Updates Hub
O RSS Store FOAF
R
Update RSS
Profile Generator
Create Profile

22. Semantic Filter
• Twitter Storm:
– Distributed realtime computation system
• Microblog Metadata
– Twitter provides metadata
• Author, date, location etc..
– Metadata Extracted
• DBpedia Entities, URLs
• Generate SPARQL Query representing interested Users
– Retrieved at Semantic Hub

23. Semantic Hub
Get Interested Subscribers
RDF
Semantic Filter Notify Update
A
N
N
O
Store and
Query Topics
RDF
Semantic
T
A
T
Fetch Updates Hub
O RSS Store FOAF
R
Update RSS
Profile Generator
Create Profile

24. Semantic Hub
• RSS Extension
– Preference – to include the SPARQL queries
• Push content
– FOAF profiles of the subscribers are matched with the
preference
– Interested subscribers receive the content

25. DERI’s Unit for Social Software
(USS)
Unit leader: John Breslin

26. Overview of research activities
• Research team at DERI
– Two postdocs (plus one starting on Monday)
• Alex Passant (10%), Maciej Dabrowski, Bahareh Heravi
– Nine PhD students
• Six supervised by John, two by Alex, one by Michael H
• Various interdisciplinary collaborations
– Exercise, e-government, political science, journalism

27. Current students
David Crowley Ted Vickey
• Citizen sensors • Exercise adherence via
– Funded by College of social networks
Engineering and Informatics – Funded by American Council
• Attaching data from on Exercise and IRCSET
sensors to social web • Developing a classification
content using semantic for fitness tweets to see if
technologies sharing exercise regimes
can encourage others

28. Current students
Antonio Aguilar (EEE) Fabrizio Orlandi
• Heart rate variability • User profiling on the Social
analysis Semantic Web
– Funded by Assisted Ambient – Funded by Cisco Foundation
Living eCAALYX EU project and IRCSET
• Developing methods to • Consolidating user profiles
help predict sudden from various platforms and
cardiac death using non- deriving interests from
linear algorithms amalgamation

29. Current students
Lukasz Porwol Owen Sacco
• e-Participation via social • Trust, accountability and
media privacy via Linked Data
– Funded by Science – Funded by Cisco Foundation
Foundation Ireland and IRCSET
• Leveraging popular • Developing privacy
networks for e-government preference managers for
instead of standalone the Semantic Web
platforms • Collaboration with US
Government

30. Current students
Marie Boran Jodi Schneider
• Connecting data journalists • Argumentative discussions
with linked scientific data – Funded by Science
– Funded by Science Foundation Ireland
Foundation Ireland • Representing, classifying
• Bridging the gap between and visualizing
experimental data from argumentative discussions
scientists and the on the Web
mainstream media

31. Current students
Myriam Leggieri
• Linked sensor data
– Funded by SPITFIRE
• Connecting sensor data
with explanatory facts from
the Linked Open Data
Cloud

32. Some past postgraduate students
• Sheila Kinsella
– ECE graduate, now engineer with Datahug
• Haklae Kim
– Now senior engineer with Samsung
• Uldis Bojars
– Now with the National Library of Latvia
• Gerard Cahill
– BSc IT graduate, now developer with Starlight

33. DERI – House
DERI Applied
Commercialisation
Research
eBusiness
eLearning
Financial Services
Health Care Green &
eGovernment
Life Sciences Sustainable IT Linked
Data
Research
Stream 1: Stream 2: Semantic Stream 3: Semantic Stream 4: Semantic Centre
Semantic Search Collaboration Information Mining Middleware
Information Sensor
Reasoning and Semantic Colla- Mining Middleware
Querying borative Software and Retrieval
Data Intensive Natural Language Service Oriented
Social Software Processing Architecture
Infrastructure

34. Thanks!
• Contacts:
- fabrizio.orlandi@deri.org
- Twitter: BadmotorF

36. Some additional stats…
• On average for:
– 200 Tweets
– 200 Facebook posts, and items.
• ~106 interests - DBpedia instances
• ~720 interests - DBpedia categories (~6.8 times more)
• Estimated average Recall: 0.74
• 22 users