Session 1: Chair - Prasan Roy
A SQL Database System for Solving Constraints
An interesting take on enhancing SQL to solve constraint problems
Acquiring Advanced Properties in Ontology Mapping
Using ontologies to improve knowledge management
Social Capital in Online Communities
This was my presentation. ;)
Session 2: Chair - Aparna Varde
Concept Search in Urdu - interesting challenges. He proposes to write a language specific stemmer to be used for the Urdu language
Topic Models and a Revisit of Text-related Applications
An Extended Cooperative Transaction Model for XML
Session 3: Chair - Anisoara Nica
The Benefit of additional Semantics in Folksonomy Systems
Exploiting additional context in folksonomies (abel@L3S.de)
Ideas: GroupMe, Social HITS, Automating MOAT, relations between tag assignments
MOAT - Meaning of a Tag (automatic MOAT using context of resource), MOAT server, DBPedia
A Microscopic View on Community Detection in Complex Networks - No Show
Towards Privacy-Preserving Integration of Distributed Heterogeneous Data
Privacy-Perserving Data Sharing Architecture. Pawel Jurczyk presented a fairly complex system which hopes to solve the problem of preserving privacy when sharing data. This approach could be applied to hospitals that wish to share data in order to make use of one another's data.
Concurrency Control and Recovery for Multiversion Database Structures
Tuukka Haapasalo (thaapasa@cs.hut.fi) proposes a solution for multiversion databases. Propositions: 1) extend B-Trees: TSBT, Transactional MVBT, or 2) Two-dimensional R-tree.
Thursday, October 30, 2008
Wednesday, October 22, 2008
Web Startup Group Meets Thursday Night
The first official Web Startup Group meeting is tomorrow night. It should be a fun event that good things will come from. It will be at 7:00 PM in the TMCB at Brigham Young University. All interested are welcome to attend.
the updated logo
the updated logoWednesday, October 15, 2008
Security Analysis of Reputation Systems
I came across this report on reputation-based systems today which I found at a reputation based social capital blog. It highlights the security threats against current reputation systems, use cases, and even ten recommendations to combat these threats.
Snapshot of the some of the recommendationsFriday, October 10, 2008
Information Pathways in Social Networks
The first talk presented in the social network session of KDD 2008 was for an interesting paper by G. Kossinets, J. Kleinberg, and D. Watts titled The Structure of Information Pathways in a Social Communication Network (PDF). Although I was not at KDD I was able to watch it online at videolectures.net.
Kleinberg, the presenter, made some interesting observations having to do with our "rhythmic" everyday conversations. The approach to analyzing communication within these social networks is focused on the frequency of correspondence, rather than the content conveyed.
They measure "distance" between individuals by measuring the minimum time required for information to pass from one node to another. A methodology based on Lamport's work and vector clocks in the area of distributed computing.
Using this metric they are able to filter a busy network (one having edges for all communication packets) in a simplified network that contains only the edges that are minimum-delay paths between a pair of nodes. They call this simplified network view the network backbone. Below is an example of such a network (along with the caption) taken from the paper.
The nodes further outside of the center of the graph are more "out-of-date" with respect to node v, since they communicate less frequently.
I found the approach to be novel and useful. As with nearly any analysis technique, caution should be used in selecting the time-period and group size to be studied. Recency and frequency issues come into play as correspondence is aggregated. However, this pursuit offers another approach for more fully understanding information flow.
Kleinberg, the presenter, made some interesting observations having to do with our "rhythmic" everyday conversations. The approach to analyzing communication within these social networks is focused on the frequency of correspondence, rather than the content conveyed.They measure "distance" between individuals by measuring the minimum time required for information to pass from one node to another. A methodology based on Lamport's work and vector clocks in the area of distributed computing.
Using this metric they are able to filter a busy network (one having edges for all communication packets) in a simplified network that contains only the edges that are minimum-delay paths between a pair of nodes. They call this simplified network view the network backbone. Below is an example of such a network (along with the caption) taken from the paper.
The nodes further outside of the center of the graph are more "out-of-date" with respect to node v, since they communicate less frequently.I found the approach to be novel and useful. As with nearly any analysis technique, caution should be used in selecting the time-period and group size to be studied. Recency and frequency issues come into play as correspondence is aggregated. However, this pursuit offers another approach for more fully understanding information flow.
Monday, October 06, 2008
Revision Control
If you worked on software in collaboration with multiple developers, then you've probably used (or wished you used) some sort of revision control system. The Google Search Volume Index plot below suggests some trends surrounding the currently available tools.
(Note: by no means is this very scientific, due to the fact that people searching with these terms could have been searching for something entirely different.)
CVS, although huge in its time, is on the decline, while SVN, Git, and Mercurial are on the rise. I have used plenty of CVS and SVN to be ready for change. I am now using Git which I have really liked so far. If you have already been using SVN as I had, I would recommend the Git-SVN Crash course to get started quickly.
(Note: by no means is this very scientific, due to the fact that people searching with these terms could have been searching for something entirely different.)
CVS, although huge in its time, is on the decline, while SVN, Git, and Mercurial are on the rise. I have used plenty of CVS and SVN to be ready for change. I am now using Git which I have really liked so far. If you have already been using SVN as I had, I would recommend the Git-SVN Crash course to get started quickly.
Thursday, October 02, 2008
Facebook growth rising past MySpace
From my local perspective Facebook has been on the rise --- I've noticed that many of my less computer savvy friends have now joined Facebook. I wondered if this trend was global, so I decided to investigate...
During the past few years MySpace has been the dominant social network, however, Facebook has continued to grow much quicker and is expected to become the leading social network. The first plot below (Figure 1) shows a comparison of searches for the keywords "facebook" and "myspace". Lately, for most of 2008, Facebook has been getting a little more attention in the news (lower portion of Figure 1) and has achieved a significantly higher search volume index.
Figure 1. Search Volume Index Comparison of 'facebook' and 'myspace'
(source: Google Trends)
Figure 2 shows the massive popularity of MySpace which began late in 2004, peaked in the middle of 2006, and has since declined --- possibly in part due to the rise of Facebook.
Figure 2. Search Volume Index of 'facebook.com' and 'myspace.com'
(source: Google Trends)
Finally, Figure 3 shows the number of daily unique visitors to Facebook as being more than that of MySpace as far back as November of 2007. (I'm not sure, but I would guess these figures to be based upon Google search result click-thrus)
Figure 3. Daily Unique Visitors of 'facebook' and 'myspace'
(source: Google Trends)
I find it very interesting to see how quickly social networks grow and evolve. As an aside, I think that Facebook is doing things more efficiently and currently providing a better service.
During the past few years MySpace has been the dominant social network, however, Facebook has continued to grow much quicker and is expected to become the leading social network. The first plot below (Figure 1) shows a comparison of searches for the keywords "facebook" and "myspace". Lately, for most of 2008, Facebook has been getting a little more attention in the news (lower portion of Figure 1) and has achieved a significantly higher search volume index.
Figure 1. Search Volume Index Comparison of 'facebook' and 'myspace'(source: Google Trends)
Figure 2 shows the massive popularity of MySpace which began late in 2004, peaked in the middle of 2006, and has since declined --- possibly in part due to the rise of Facebook.
Figure 2. Search Volume Index of 'facebook.com' and 'myspace.com'(source: Google Trends)
Figure 3. Daily Unique Visitors of 'facebook' and 'myspace'(source: Google Trends)
I find it very interesting to see how quickly social networks grow and evolve. As an aside, I think that Facebook is doing things more efficiently and currently providing a better service.
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