User Profiling on the Social

Semantic Web

Fabrizio Orlandi, DERI (NUI Galway, Ireland)

Kno.e.sis – WSU Dayton, OH – 9 Feb 2012

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]

[1] S. Schiaffino, A. Amandi. 2009.

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.

• 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?

Research Questions

Challenges – 1

• Information on the Social Web is stored in isolated data silos on

heterogeneous and disconnected social media websites

http://www.w3.org

Challenges – 2

• The Web of Data: a continuously evolving “open corpus”

LOD Cloud by R. Cyganiak and

A. Jentzsch

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

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]

Outline

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

12

3

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…

Semantic Personalization of Social

Web Streams

Motivation

Twitter – Growth

Information Overload

11http://www.cmswire.com/cms/customer-experience/35-key-twitter-statistics-infographic-012384.php

Motivation

• How many people should I follow?

• Am I receiving latest/complete information?

• How can I quickly tell the system what are my interests?

Approach -- Overview

Football

Apple

User

Profiles

Filter

BroadcastThe new

iPhone has a

3.5-inch screen,

released today

Semantic Filter

Semantic

Hub

Profile Generator

RDF

A

N

N

O

T

A

T

O

R

RDF

RSS

Store and

Query Topics

Notify Update

Fetch Updates

Get Interested

Subscribers

Create Profile

Store FOAF

The new

iPhone has a 3.5-

inch screen,

released today

Annotate: iPhone

?user foaf:interest

dbPedia:iPhone

Union

?user foaf:interest

Category:Apple

Get

Subscribers

based on

preference

Push Updates

to Interested

Users

Update RSS

User Profiling

User Profile

Interlink social websites

Merge and model user data

Personalise users’ experience

using their profile

Integration&

User Modelling

Recommendations

Search Personalisation

Adaptive Systems

User Profiling

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

Semantic Filter

Semantic

Hub

Profile Generator

RDF

A

N

N

O

T

A

T

O

R

RDF

RSS

Store and

Query Topics

Notify Update

Fetch Updates

Get Interested Subscribers

Create Profile

Store FOAFUpdate RSS

Semantic Filter

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

Semantic Filter

Semantic

Hub

Profile Generator

RDF

A

N

N

O

T

A

T

O

R

RDF

RSS

Store and

Query Topics

Notify Update

Fetch Updates

Get Interested Subscribers

Create Profile

Store FOAFUpdate RSS

Semantic Hub

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

DERI’s Unit for Social Software

(USS)

Unit leader: John Breslin

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

Current students

David Crowley

• Citizen sensors

– Funded by College of

Engineering and Informatics

• Attaching data from

sensors to social web

content using semantic

technologies

Ted Vickey

• Exercise adherence via

social networks

– Funded by American Council

on Exercise and IRCSET

• Developing a classification

for fitness tweets to see if

sharing exercise regimes

can encourage others

Current students

Antonio Aguilar (EEE)

• Heart rate variability

analysis

– Funded by Assisted Ambient

Living eCAALYX EU project

• Developing methods to

help predict sudden

cardiac death using non-

linear algorithms

Fabrizio Orlandi

• User profiling on the Social

Semantic Web

– Funded by Cisco Foundation

and IRCSET

• Consolidating user profiles

from various platforms and

deriving interests from

amalgamation

Current students

Lukasz Porwol

• e-Participation via social

media

– Funded by Science

Foundation Ireland

• Leveraging popular

networks for e-government

instead of standalone

platforms

Owen Sacco

• Trust, accountability and

privacy via Linked Data

– Funded by Cisco Foundation

and IRCSET

• Developing privacy

preference managers for

the Semantic Web

• Collaboration with US

Government

Current students

Marie Boran

• Connecting data journalists

with linked scientific data

– Funded by Science

Foundation Ireland

• Bridging the gap between

experimental data from

scientists and the

mainstream media

Jodi Schneider

• Argumentative discussions

– Funded by Science

Foundation Ireland

• Representing, classifying

and visualizing

argumentative discussions

on the Web

Current students

Myriam Leggieri

• Linked sensor data

– Funded by SPITFIRE

• Connecting sensor data

with explanatory facts from

the Linked Open Data

Cloud

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

DERI – House

eBusiness

Financial Services

Health Care

Life Sciences

eLearning

Green &

Sustainable ITeGovernment

Stream 3: Semantic

Information Mining

Information

Mining

and Retrieval

Natural Language

Processing

Stream 1:

Semantic Search

Reasoning and

Querying

Data Intensive

Infrastructure

Stream 2: Semantic

Collaboration

Semantic Colla-

borative Software

Social Software

Stream 4: Semantic

Middleware

Service Oriented

Architecture

Sensor

Middleware

Linked

Data

Research

Centre

DERI Applied

ResearchCommercialisation

Thanks!

• Contacts:

- fabrizio.orlandi@deri.org

- Twitter: BadmotorF

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