Many term weighting methods are suggested in the literature for Information Retrieval and Text Categorization. Term weighting method, a part of feature selection process is not yet explored for URL classification problem. We classify a web page using its URL alone without fetching its content and hence URL based classification is faster than other methods. In this study, we investigate the use ...

In this paper a new method for the design of a linear phase distributed amplifier in 180nm CMOS technology is presented. The method is based on analogy between transversal filters and distributed amplifiers topologies. In the proposed method the linearity of the phase at frequency range of 0-50 GHz is obtained by using proper weighting factors for each gain stage in cascaded amplifier topology....

The importance of good weighting methodology in information retrieval methods – the method that affects the most useful features of a document or query representative is examined. Good weighting methodologies are supposed to be more important than the feature selection process. Weighting features is the thing that many information retrieval systems are regarding as being of minor importance as ...

This article presents our contributions to expert search and discussion search of Enterprise Track in TREC 2006. In discussion search, we take advantage of the redundant patterns of emails, such as the subject, author, sent time, etc., which we incorporate in a field-based weighting method to mine discussion topics with more robustness. Some non-content features, such as time-line and mail thre...

This paper presents a new random weighting method for estimation of Poisson distributions. A theory is established for random weighting estimation of the population parameters of two Poisson distributions with partially missing data. The strong convergence of the random weighting estimation is rigorously proved under the condition of 1 1 E X     (0 1)    . The random weighting estimation...

A new method of feature weighting, useful also for feature selection has been described. It is quite efficient and gives quite accurate results. In general weighting algorithm may be used with any kind of learning algorithm. The weighting algorithm with k-nearest neighbors model was used to estimate the optimal feature base for a given distance measure. Results obtained with this algorithm clea...

The propensity score method is frequently used to deal with bias from standard regression in observational studies. The propensity score method involves calculating the conditional probability (propensity) of being in the treated group (of the exposure) given a set of covariates, weighting (or sampling) the data based on these propensity scores, and then analyzing the outcome using the weighted...

We have proposed an improved method for calculating surface tension of liquid-vapour interface based on the thermodynamic route. This method combines the central difference scheme used in the test-area method and the Bennett weighting factor. This improved method shows faster convergence than the test area method as the weighting factor reduces the asymmetric bias of two perturbations. In addit...