Bilal Zaka

Automatically Detecting Points of Interest and Social Networks from Tracking Positions of Avatars in a Virtual World

With hundreds of millions of users already today,virtual worlds will become an important factor in tomorrows media landscape. In a virtual world, users are represented by so-called avatars. These avatars move around the virtual world, communicate with each other,and interact with the virtual world. The movements of these avatars can be tracked precisely, and useful information can be inferred from analyzing these movements. In this paper, we analyze a large data set (≫200 million records) of position data describing the movements of avatars in the virtual world Second Life.The dataset was derived from in-world sensors that had been deployed beforehand, but also so-called bots can be used to gather such information. From this data, we can track usage patterns of avatars (and therefore users) overtime. We can also identify regions of high interest where a large number of users gather frequently (which would be important for planning advertising in the virtual world), and visualize this statistical analysis using heat maps. By combining the position data with information about the language spoken by the avatars, we can label these regions according to the language predominantly spoken there. Analyzing incidents of co-location of avatars over a period of time, we can automatically infer friends, and eventually social networks. Using additional metadata such as language we can label clusters in this automatically generated social network.

A Geospatial Wiki for m-Learning

In subjects, where a major part of the education is based on visual information, like geosciences, architecture or civil engineering, this information is often tied to a specific location. Field studies and excursions are thus an essential part of the education in such subjects. This paper describes an application designed to bring the advantages of collaborative, technology enhanced learning into these environments. The development is based on the idea of a Wiki specially designed for collaboratively compiling location-bound information. Other key features are the inclusion geographic coordinates to all Wiki articles, the integration of external map material and providinga mobile interface for the use ldquoin the fieldrdquo. The result of this development process is a geoWiki application tailored for the needs of m-Learning. With a user interface based on widely known applications, TUGeoWiki offers learners and teachers alike the possibility to collaborate on geospatial information.

Framework for extending plagiarism detection in virtual worlds

The economies of virtual worlds are driven by the exchange of virtual good and services. These goods are available in the form of image textures, 3D objects, and scripts. The theft or unauthorized use of these goods was and still is a serious problem for virtual world users and content providers. In our work we try to point out various aspects of IPR violations in virtual worlds and suggest a platform for detection inspired by plagiarism detection services in real world.

Emerging Web Based Learning Systems and Scalability Issues

The recent yearspsila changes in the Web and its application have also had an enormous impact on learning. This paper discusses a shift of Web based learning systems towards scalable web learning services. It provides an overview of current state of development and evolution path of Web based learning systems. Desired characteristics of modern systems are identified and role of service oriented computing (SOC) to support this development is exemplified.

Personalized Interactive Newscast (PINC): Towards a Multimodal Interface for Personalized News

The contemporary information infrastructure gives way to a massive offer of news sources and subsequently news contents. Finding such sources and filtering relevant news according to personal preferences is a time-consuming task in the daily effort to stay informed. Moreover many of these sources are not accessible when spare time to read news is available, especially while being en-route. Personalized interactive newscast (PINC) is a system which aggregates vast numbers of news contents and associates them by semantic equivalence. By filtering and arranging by personal preferences a personal newscast is created, embracing recommendations for interesting news articles. This newscast is made accessible via various interfaces to provide a central source of information which is accessible in most situations.