I’m glad to say that the TRECK track of SAC went quite well and did not suffer from some of the things I mentioned in my previous rant. The track was organized by Dr. Jean-Marc Seigneur of the University of Geneva, and the two sessions were chaired by Dr. Virgilio Almeida of the Federal University of Minas Gerais (who I had an interesting discussion with after the track), and was broadly divided into two themes: trust and recommender systems. The trust session had an overall focus on peer-to-peer systems, here are some quick samples:

“Propagating Multitrust Within Trust Networks,” Bistarelli/Santini

Francesco Santini presented the idea of multitrust, which aims at computing trust in a dynamically created group of trustees who all have different subjective trust values.

“Autonomic Trust Reasoning Enables Misbehavior Detection in OLSR,” Adnane/Timoteo de Sousa/Bidan/Me’

Asmaa Adnane presented the application of trust to detecting misbehaviour in link-state routing algorithms. I always wonder how well these cool ideas will work in practice; if information is lost or delayed they will deduce that another node is untrustworthy!

“Surework: A Super-peer Reputation Framework for p2p Networks,” Rodriguez-Perez/Esparza/Munoz

The Surework Framework extended the current operation of trust in p2p networks to include the idea of super-peers; nodes with very high reputation can, in fact, become reputation servers.

“CAT: A Context-Aware Trust Model for Open and Dynamic Systems” Uddin/Zulkernine/Ahamed

The CAT Model was introduced and explained- it is a model of open and dynamic systems that considers services as contexts.. The 15 minute time-limit was a bit constraining and I’ll have to read the full paper!

“Examining the Motivations of Defection in Large-Scale Open Systems,” Martin-Hughes/Renz

Rowan Martin-Hughes applied a game-theoretic analysis to understand why people would defect in a large-scale open system, like eBay. The analysis was based on a modified version of the Prisoner’s dilemma, which was very interesting; the only question that arises is, as Daniele mentioned, is this appropriate when users may very well behave irrationally?

The second session focused on recommender systems:

“Tag-Aware Recommender Systems by Fusion of Collaborative Filtering Algorithms,” Tso-Sutter/Marinho/Schmidt-Thieme

Karen Tso-Sutter presented her work on combining user-item tags into the collaborative filtering process. Interestingly, tags did not improve accuracy until the algorithm was already boosted by using both user- and item- based algorithms.

“The Effect of Correlation Coefficients on Communities of Recommenders,” Lathia/Hailes/Capra

My work! Looking at the similarity distribution over a graph generated by a nearest-neighbour algorithm.

“Whom Should I Trust? The Impact of Key Figures on Cold-Start Recommendations,” Victor/Cornelis/Teredesai/De Cock

Patricia Victor’s paper discussed an extension to Paolo Massa’s work on trust-aware recommender systems, which concluded that the cold-start problem in recommender systems can be avoided by having users express trust values in other users, which can then be propagated. The problem is: which users should they connect to? The paper has an interesting analysis of the different kind of users in the epinions dataset.

“Comparing Keywords and Taxonomies in the Representation of Users Profiles in a Content-Based Recommender System” Loh/Lorenzi/Simoes/Wives/Oliveira

The last paper veered away from collaborative filtering to look at the role of keywords and taxonomies in content-based recommender systems. The taxonomy vs. folksonomy war continues!

The full list of abstracts can be read on the trustcomp-treck web site. If any of the attendees or authors are reading this post: we welcome your thoughts and comments, and officially invite you to contribute to this blog! To write a guest-post about your research, please get in touch! (n.lathia @ cs.ucl.ac.uk)