Tag Archives: PhD

(Late) report on FOAF workshop

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The FOAF workshop in Galway was almost 20 days ago, so the following report is a little bit late. Hope it can be useful at least as an historical memory.
It was fantastic to meet in flesh many people I just learnt to appreciate through their blogs. Many of the papers were very interesting. I especially like the idea of “Semantic cookies” (you keep your profile [as FOAF file] in a cookie and, with some trick, you give access to every site to it, sites can read it and give you a personalized experience) and “Bootstrapping the FOAF-Web: An Experiment in Social Network Mining” by Peter Mika (the idea is to use Google to infer social relationships among people). And there was also my paper of course. The presentation was so and so, I think I try to put too many concepts for a 15 minutes presentation. The only stuff I liked was the subtitle I wrote at the last second on the first slide: “Moleskiing: Climbing the peaks of FOAF”.
Almost half of the workshop was devoted to very interesting Breakout sessions.
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Paper accepted for Coopis → looking for cheap place in Cyprus (through 2 degrees of separation)

Good news: my paper “Trust-aware Collaborative Filtering for Recommender Systems” got accepted for Coopis2004.
Bad news: the conference is hyper-expensive.
So I’m looking for hyper-cheap (possibly free) hospitality in Larnaca, Cyprus, from 25 Oct to 29 Oct 2004. I checked on couchsurfing (a site where people offers ospitality in their houses and a super-cool YASN [yes, you can express your friends list]) but I found none in Cyprus.
If we take for true the six degree of separation theorem, I should be connected to everyone in Cyprus by only six degrees of separation. So I guess there should be at least some cypriots in my friends of friends set, now i only need to find one of the connecting friends. So if you know someone in Cyprus, please become my friend and close the circuit (and don’t forget to write down the path from me to the cypriot host in the comments below). Thanks.

Call For Papers: 1st Workshop on Friend of a Friend, Social Networking and the Semantic Web

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1st Workshop on Friend of a Friend, Social Networking and the Semantic Web (FOAF’2004)
*1-2 September 2004, Galway, Ireland*,
sponsored by SWAD-Europe and DERI
http://www.w3.org/2001/sw/Europe/events/foaf-galway/

Many of the interesting conferences about these topics happen in USA. So, if you are in Europe, you cannot miss this one!
In the committee there are many people that I learn to know by email or by reading their blogs but I have never met. I hope to meet them physically in Galway.
(found via rdfweb mailing list)

This call for papers also appears in the Call for papers topicexchange channel and in Trust-related-conferences wiki page
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Workshops Committees

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I’m writing a paper for Coopis2004 and have not too much time to blog. By the way, I’m in committee of 2 very interesting workshops:
– Trust, Security, and Reputation on the Semantic Web (held at the 3rd International Semantic Web Conference (ISWC) from 7-11 November, 2004 in Hiroshima, Japan.)
Deadline for Submissions: July 16, 2004
– Trust, Recommendations, Evidence and other Collaboration Know-how (TRECK) Track (track of the 20th ACM Symposium on Applied Computing, Santa Fe, New Mexico, March 13 -17, 2005)
Deadline for Submissions: Sept. 3, 2004

You are of course invited to submit challenging and innovative ideas!
I guess I should also update our wiki list of trust related conferences. In the meantime I ping http://topicexchange.com/t/calls_for_papers/

Jung (Java Universal Network/Graph Framework)

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For my studies on trust metrics, I need to code trust metrics. I was looking for a Java package for modeling, analysis, and visualization of graphs (possibly weighted and directed). I tried many of them (see below) but I found a wonderful one!
Java Universal Network/Graph Framework hosted on SourceForge so open source under a BSD licence (javadoc).
JUNG — the Java Universal Network/Graph Framework–is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries.
The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances (Dijkstra Shortest Path), flows, and importance measures (centrality, PageRank, HITS, Random Walk, etc.).
JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

If you don’t trust me, you can try the Ranking Demo or the other demos.

It is of course an evolving project, I already wrote some code to draw arrows and to label edges with weights and I’m trying to integrate it. I plan to code some of these trust metrics. JUNG is maintained by some great PhD students.
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PhD Research Proposal: Trust-aware Decentralized Recommender Systems

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I realised today I didn’t write yet an entry about my PhD Research Proposal “Trust-aware Decentralized Recommender Systems” (TaDRS).
So here it is the PDF file. If you have any comment or criticism, I’ll be happy to hear from you.
The PhD research proposal is a little bit outdated (29th May 2003) but I didn’t have a blog at that time. Enjoy and let me know what you think.

UPDATE:
Abstract
This PhD thesis addresses the following problem: exploiting of trust information in order to enhance the accuracy and the user acceptance of current Recommender Systems (RS). RSs suggest to users items they will probably like. Up to now, current RSs mainly generate recommendations based on users’ opinions on items. Nowadays, with the growth of online communities, e-marketplaces, weblogs and peer-to-peer networks, a new kind of information is available: rating expressed by an user on another user (trust). We analyze current RS weaknesses and show how use of trust can overcome them. We proposed a solution about exploiting of trust into RSs and underline what experiments we will run in order to test our solution.

Paper submitted to iTrust2004

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I submitted my paper Using Trust in Recommender Systems: an Experimental Analysis to the Second International Conference on Trust Management 2004.
You can read the PDF file or the HTML version (by latex2html).

Abstract:
Recommender systems (RS) have been used for suggesting items (movies, books, songs, etc.) that users might like. RSs compute a user similarity between users and use this as a weight for the users’ ratings. However they have many weaknesses, such as sparseness, cold start and vulnerability to attacks. We assert that these weaknesses can be alleviated using a Trust-aware system that takes into account the “web of trust” provided by every user.
Specifically, we analyze data from the popular Internet web site epinions.com. The dataset consists of 49290 users who expressed reviews (with rating) on items and explicitly specified their web of trust, i.e. users whose reviews they have consistently found to be valuable.
We show that users have usually few items rated in commons. For this reason, the classic RS technique is often ineffective and is not able to compute a user similarity weight for many of the users. Instead exploiting the webs of trust, it is possible to propagate trust and infer an additional weight for other users. We show how this quantity can be computed against a larger number of users.