Social Network Games with Obligatory Product Selection

Recently, Apt and Markakis introduced a model for product adoption in social networks with multiple products, where the agents, influenced by their neighbours, can adopt one out of several alternatives (products). To analyze these networks we introduce social network games in which product adoption is obligatory. We show that when the underlying graph is a simple cycle, there is a polynomial time algorithm allowing us to determine whether the game has a Nash equilibrium. In contrast, in the arbitrary case this problem is NP-complete. We also show that the problem of determining whether the game is weakly acyclic is co-NP hard. Using these games we analyze various types of paradoxes that can arise in the considered networks. One of them corresponds to the well-known Braess paradox in congestion games. In particular, we show that social networks exist with the property that by adding an additional product to a specific node, the choices of the nodes will unavoidably evolve in such a way that everybody is strictly worse off.Comment: In Proceedings GandALF 2013, arXiv:1307.416

A cluster-based simulation of facet-based search

The recent increase of online video has challenged the research in the field of video information retrieval. Video search engines are becoming more and more interactive, helping the user to easily find what he or she is looking for. In this poster, we present a new approach of using an iterative clustering algorithm on text and visual features to simulate users creating new facets in a facet-based interface. Our experimental results prove the usefulness of such an approach

Exploiting log files in video retrieval

While research into user-centered text retrieval is based on mature evaluation methodologies, user evaluation in multimedia retrieval is still in its infancy. User evaluations can be expensive and are also often non-repeatable. An alternative way of evaluating such systems is the use of simulations. In this poster, we present an evaluation methodology which is based on exploiting log files recorded from a user-study we conducted

Simulated evaluation of faceted browsing based on feature selection

In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness