The availability of huge amount of graph-like data poses several data management challenges related to the representation, storage and querying of such data. On one hand, we have standards such as the Resource Description Framework and database solutions optimised for graph-like data. On the other hand, we have graph languages offering different trade-offs between expressiveness and complexity of query evaluation.
The way in which companies benefit from open source software (OSS) communities varies and corresponds with the business strategy they maintain. One way of establishing influence in OSS communities is by deploying own resources to an OSS project. Assigning own paid developers to work for an OSS project, like the Linux kernel project, is a suitable means to influence project work. On the other hand, the pertinent literature on user communities and governance in OSS maintains that a large proportion of influence individuals have in a community depends on their position in the community. In this talk, I will give an update on my ongoing work on analyzing firm-sponsored developers, which are active in the Linux kernel community.
The Multi-Agent Programming Contest is an international competition taking place every year with the goal to encourage multi-agent research. Our research lab was able to participate in it.
The Semantic Web is intended as a web of machine readable data where every data source can be the data provider for different kinds of applica- tions. However, due to a lack of support it is still cumbersome to work with RDF data in modern, object-oriented programming languages.
In this talk, I will present my recent work on visualization on networks. I'll show a series of old and new ways of drawing graphs, from KONECT, SocialSensor and work on LiquidFeedback. The presentation will show: (a) Drawing networks with the Laplacian.
While the Web was initiated to better support scientists at CERN it has since grown to a gigantic global information and communication medium used by billions of people.
Predicting and explaining the formation and dissolution of ties in social networks requires a deep understanding of the sociological factors that drive the linkage dynamics in social systems. In this paper, we present a computational social science approach that translates sociological concepts to structural measures on directed link and unlink networks.
We review existing models for modelling links between documents and show parallels to the multi-Dirichlet based topic model. The second part of my talk is about applications of multi-Dirichlet models in modelling documents with citations, log files and user profiles of a social network.
AbstractSwarm allows graphical modeling and simulation of problems from different domains as multi-agent systems. Simulations and their results are visualized across problem domains without the need to define a specific scheme for a concrete problem.
We introduce our implementation of the STAR algorithm and recent experiment results of its performance. The STAR algorithm is used for relationship query over large relationship graphs, which can be considered from algorithmic point of view as a Steiner Tree problem.