This paper present the participation details of DEMIR (Dokuz Eylul University Multimedia Information Retrieval) research team at ImageCLEFwiki2011. This year we investigate on evaluating of different weighting models on text retrieval performance. In the case of low-level feature selection, we extracted different features and examined their performance to choose the proper feature for our exper...

consists of a small knowledge-based system teaching and assisting designers of interactive applications in selecting appropriate interaction styles for a particular context of use. As any other tool for working with guidelines, five development milestones have been browsed. Guidelines for selecting interaction styles have been captured in a knowledge-base system as selections among an available...

This note considers variable selection in the robust linear model via R-estimates. The proposed rank-based approach is a generalization of the penalized least squares estimators where we replace the least squares loss function with Jaeckel’s (1972) dispersion function. Our rank-based method is robust to outliers in the errors and has roots in traditional nonparametric statistics for simple loca...

Model selection is linked to model assessment, which is the problem of comparing different models, or model parameters, for a specific learning task. For supervised learning, the standard practical technique is crossvalidation, which is not applicable for semi-supervised and unsupervised settings. In this paper, a new model assessment scheme is introduced which is based on a notion of stability...

In many cases complex scenes are composed of densely occluded objects, which means that only a small fraction of the scene is visible, while the remaining parts are occluded. This property can be exploited to accelerate rendering by simply removing most of the hidden parts before sending the polygons to the graphics hardware. In recent years, a lot of so called occlusion-culling methods have be...

Obtaining informative answer passages and ranking them appropriately has previously been error prone for complex, non-factoid questions related to action and event occurrences, causes, and spatiotemporal attributes. A fundamental problem that has hampered the efforts to date has been the inability to extract relations of interest that determine the search for relevant answer passages. We report...

Feature selection is a topic of great interest in applications dealing with high-dimensional datasets. These applications include gene expression array analysis, combinatorial chemistry and text processing of online documents. Using feature selection brings about several advantages. First, it leads to lower computational cost and time. Less memory is needed to store the data and less processing...

Creating case representations in unsupervised textual case-based reasoning applications is a challenging task because class knowledge is not available to aid selection of discriminatory features or to evaluate alternative system design configurations. Representation is considered as part of the development of a tool, called CAM, which supports an anomaly report processing task for the European ...

Similarity measurement is a critical component in any case-based reasoning (CBR) system. CBR is a superior technique for solving new problems based on previous experiences. Main assumption in CBR relies on the hypothesis that states similar problems should have similar solutions. This paper describes a comparative analysis on several commonly used similarity measures (Canberra, Clark, and Norma...

“Human Computation” represents a new paradigm of applications that exploit people’s desire to be entertained by outsourcing certain steps of the computational process to the players. Such applications also produce useful metadata as a by-product. Games With A Purpose (GWAP) demonstrate the potential of human computation to solve a variety of problems that computer computation cannot currently r...