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Presented at JTEL Summer School 2010
Citation preview
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Trust Modeling and Evaluation in Web 2.0 Collaborative Learning Social Software
Na Li
Swiss Federal Institute of Technology in Lausanne (EPFL)
JTEL 2010 June 7-June 11
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Outline
• Research Questions • Current Progress • Future Work
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Research Questions • Lots of Web 2.0 learning environments bring about large
amount of user-generated content ▫ What should we trust? ▫ Who should we trust?
RSS Feeds
Pictures
Documents
Videos
Wiki Pages
Pictures
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Research Questions • Trust Measurement ▫ Evaluate quality of user-generated content ▫ Recommend useful resources ▫ Privacy management
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Current Progress
• Trust-based rating prediction ▫ Quality evaluation in open learning
environment ▫ Filter helpful learning resources, people and
group activities
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Trust-Based Rating Prediction Approach
• Basic idea ▫ What influences rating opinion: similarity and
familiarity ▫ People tend to trust the opinions of
acquaintance and those having similar interests and tastes.
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Trust-Based Rating Prediction Approach
• Trust measurement ▫ Multi-relational trust metric ▫ Build a “Web of Trust” for a particular user using
heterogeneous types of relationships
Trust
How Much?
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Trust-Based Rating Prediction Approach • Trust propagation • Propagation distance (PD)
Alice
French Learning Activity
Is Member
Article Create
Video
Propagate
Luis Has Member
Rated by Sara
Rated by Ben
Bob
Commented by
Jack Propagate Propagate
PD
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Trust-Based Rating Prediction Approach
• Rating prediction from a user to an item ▫ Using user’s “Web of Trust” ▫ People in “Web of Trust” are seen as trustable ▫ Average of all the rating scores given by trustable
people, weighted by their trust value
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Evaluation and Results • Using Remashed data set ▫ 50 users, 6000 items, 3000 tags and 450 ratings ▫ “Leave-one-out” method ▫ Compare “predicted score – actual score” deviation of
trust-based prediction and simple average
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Evaluation and Results • Change parameters ▫ Weights for relationships doesn’t make a significant
difference in rating prediction ▫ Increasing size of trust network might add noise, lead
to bigger prediction error
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Future Work
• Future deploy and evaluation will be conducted in a collaborative learning platform, namely Graaasp(graaasp.epfl.ch)
• Trust-based privacy management
Swiss Federal Institute of Technology in Lausanne EPFL, CH-1015 Lausanne, Switzerland
Questions?