This paper describes our participation in the Task understanding task of the Tasks track at TREC 2016. We introduce a general probabilistic framework in which we combine query suggestions from web search engines with keyphrases generated from top ranked documents. We achieved top performance among all submitted systems, on both official evaluation metrics, which attests the effectiveness of our...

In this paper, I review the contour grouping approaches towards segmentation of images. Classifying the existing literature into local and global methods, I show how the grouping methods have improved over time, moving from local to global and from heuristic to probabilistic. Requirements for performance evaluation of grouping algorithms are also discussed.

This paper presents a framework to detect moving objects based on the recognition of moving features in the images. The classification scheme is based on a complete probabilistic representation of feature locations that relates the vehicle motion with the visual information. Experimental evaluation under different settings in an outdoor, urban environment shows the performance of the proposed a...

background nowadays, productivity and efficiency are considered a culture and a perspective in both life and work environments. this is the starting point of human development. objectives the aim of the present study was to investigate the performance of hospitals affiliated to mashhad university of medical sciences using the pabon lasso model. methods the present study was a descriptive-analyt...

We investigate trust propagation in delegation situations, which often occur in hierarchical organisations and coalition structures. In doing so we define a delegation chain representing the sub-delegation process. Such delegation chains present a problem for current trust evaluation mechanisms, which are unable to accurately divide trust among the chain members, resulting in degraded system pe...

Entity resolution is the problem of identifying the tuples that represent the same real world entity. In this paper, we address the problem of entity resolution over probabilistic data (ERPD), which arises in many applications that have to deal with probabilistic data. To deal with the ERPD problem, we distinguish between two classes of similarity functions, i.e. context-free and context-sensit...

A framework for evaluating the performance of asynchronous systems is presented. Performance evaluation of the asynchronous circuits is a challenging process due to the dependencies between highly concurrent events. The utilized performance model is a Probabilistic Timed Petri-Net (PTPN) with possible choice places to capture the conditional behavior of the system. The proposed framework exploi...

Foreground/background segmentation is an active research area for moving object analysis. We combine two probabilistic approaches one of which estimates foreground/background probabilistic density and the other uses prior knowledge to decompose the colour space. The observed performance advantages are associated with the fusion of operators with completely different basis. Tests on outdoor and ...