In web information retrieval, the terms or keywords are used for indexing purpose of document. These terms or keywords appear in special location such as title, subtitle, header, hyperlinks and so on. Vector space model ignores the importance of these terms with respect to their position while calculating the weight of the indexing terms. The effectiveness of the vector space model crucially de...

Multiple objective decision support, either for selection among finite alternatives or for combining multiple functions in mathematical programming, often involves estimating a set of weights of relative importance. Recently Solymosi and Dombi proposed a means of estimating such weights based upon ordinal preference information. This method relies upon the centroid of bounded weights. Analytic ...

Several Multi-Criteria-Decision-Making methodologies assume the existence of weights associated with the different criteria, reflecting their relative importance. One of the most popular ways to infer such weights is the Analytic Hierarchy Process, which constructs first a matrix of pairwise comparisons, from which weights are derived following one out of many existing procedures, such as the e...

This paper presents a way to perform speaker adaptation for automatic speech recognition using the stream weights in a multi-stream setup, which included acoustic models for “Articulatory Features” such as ROUNDED or VOICED. We present supervised speaker adaptation experiments on a spontaneous speech task and compare the above stream-based approach to conventional approaches, in which the model...

In this paper we introduce a new dynamic importance sampling propagation algorithm for Bayesian networks. Importance sampling is based on using an auxiliary sampling distribution from which a set of configurations of the variables in the network is drawn, and the performance of the algorithm depends on the variance of the weights associated with the simulated configurations. The basic idea of d...

In machine-learning applications, data selection is of crucial importance if good runtime performance is to be achieved. Feature Decay Algorithms (FDA) have demonstrated excellent performance in a number of tasks. While the decay function is at the heart of the success of FDA, its parameters are initialised with the same weights. In this paper, we investigate the effect on Machine Translation o...

An approach for automatic object localization in medical images utilizing an extended version of the generalized Hough transform (GHT) is presented. In our approach the shape model in the GHT is equipped with specific model point weights, which are used in the voting process. The weights are adjusted in a discriminative training procedure, which aims at a minimal localization error of the GHT. ...

This paper proposes the modification of a technique of simultaneous optimization of multiple response variables that works using a Bayesian predictive distribution, to incorporate different weights to the response variables according to their importance in the products. To achieve this, the desirability function has been incorporated to the original proposal. This research shows by representing...