In this paper, we employed Naïve Bayes, Augmented Naïve Bayes, Tree Augmented Naïve Bayes, Sons & Spouses, Markov Blanket, Augmented Markov Blanket, Semi Supervised and Bayesian network techniques to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes...

In today world of internet, it is important to feedback the users based on what they demand. Moreover, one of the important tasks in data mining is classification. Today, there are several classification techniques in order to solve the classification problems like Genetic Algorithm, Decision Tree, Bayesian and others. In this article, it is attempted to classify researchers to “Expert” and “No...

For the present work, we deal with the significant problem of high imbalance in data in binary or multi-class classification problems. We study two different linguistic applications. The former determines whether a syntactic construction (environment) co-occurs with a verb in a natural text corpus consists a subcategorization frame of the verb or not. The latter is called Name Entity Recognitio...

Demodulation of received signals for a known channel parameters over Rayleigh fading channel is done by BEM (Bayesian Estimation Maximization) algorithm using MAP (Maximum A Posteriori) Probability decisions. Simulation results were produced using this demodulator for the specified mobile satellite based trans-receiver system to find the BER (Bit Error Rate). Comparisons are made to that of a Q...

Receivers for a variety of communication channels must often be designed to operate in the absence of channel information. While a channel estimate may be generated from training data, known data then occupies available spectrum, which is often a scarce resource. We propose a blind maximum likelihood (ML) sequence detection and decoding technique for which the receiver requires no training data...

Abst rac t . We address the question as to whether a prior distribution on the space of distribution functions exists which generates the posterior produced by Efron's and Rubin's bootstrap techniques, emphasizing the connections with the Dirichlet process. We also introduce a new resampling plan which has two advantages: prior opinions are taken into account and the predictive distribution of ...

Sequential Bayesian techniques enable tracking of evolving geophysical parameters via sequential observations. They provide a formulation in which the geophysical parameters that characterize dynamic, nonstationary processes are continuously estimated as new data become available. This is done by using prediction from previous estimates of geophysical parameters, updates stemming from physical ...