While focusing on document clustering, this work presents a fuzzy semi-supervised clustering algorithm called fuzzy semi-Kmeans. The fuzzy semi-Kmeans is an extension of K-means clustering model, and it is inspired by an EM algorithm and a Gaussian mixture model. Additionally, the fuzzy semi-Kmeans provides the flexibility to employ different fuzzy membership functions to measure the distance b...

This paper presents a stochastic graph based method for recommending or selecting a small subset of blogs that best represents a much larger set. within a certain topic. Each blog is assigned a score that reflects how representative it is. Blog scores are calculated recursively in terms of the scores of their neighbors in a lexical similarity graph. A random walk is performed on a graph where n...

In this paper, we develop data driven registration algorithms, relying on pixel similarity metrics, that enable an accurate (subpixel) rigid registration of dissimilar single or multimodal 2D/3D images. Gross dissimilarities are handled by considering similarity measures related to robust M-estimators. In particular, a novel (robust) similarity metric is proposed for comparing multimodal images...

• Sentiment Analysis (SA) requires large human labeled data; which is costly to obtain. • Domain Adaptation(DA) techniques help in performing SA with minimum human labeled data. • Two techniques, Feedback EM and Rocchio SVM are proposed for data selection/filtering. • Use of Mutual Information(MI) and Cosine Distance(CD) to measure similarity between In and Out-Domain distributions.

Local Gabor features (jets) have been widely used in face recognition systems. Once the sets of jets have been extracted from the two faces to be compared, a proper measure of similarity (or distance) between corresponding features should be chosen. For instance, in the well known Elastic Bunch Graph Matching (EBGM) approach and other Gabor-based face recognition systems, the cosine distance wa...

The need to monitor the Earth’s surface over a range of spatial and temporal scales is fundamental in ecosystems planning and management. Change-Vector Analysis (CVA) is a bi-temporal method of change detection that considers the magnitude and direction of change vector. However, many multispectral applications do not make use of the direction component. The procedure most used to calculate the...

Various distance-based clustering algorithms have been reported, but the core component of all them is a similarity or distance measure for classification data. Rather than setting priority to comparison performance different algorithms, it may be worthy analyze influence measures on results algorithms. The main contribution this work comparative study impact 9 similarity-based trajectory using...

Despite the development of new imaging techniques, existing X-ray data remain an appropriate tool to study speech production phenomena. However, to exploit these images, the shapes of the vocal tract articulators must first be extracted. This task, usually manually realized, is long and laborious. This paper describes a semi-automatic technique for facilitating the extraction of vocal tract con...

In present scenario, the software companies are frequently involving test effort estimation to allocate resources efficiently during development process. Different machine learning models developed estimate total that would be required before product could delivered. These computational used use past data efforts. current studies, for is predicted using Genetic algorithm and Neural Network. The...