Keyword Extraction is the process of assigning keywords to a document where the important words are selected by the system automatically. This proposed frame work is used to extract the keywords using Fuzzy logic method from Meeting Transcripts. At first, the given input is preprocessed. Subsequently, the preprocessed data will be sent to the features extraction method. In this method three fea...

In this paper, we propose four techniques for extraction of facial features namely 2DPCA, LDA, KPCA and KFA. The purpose of face feature extraction is to capture certain discriminative features that are unique for a person. In the previous works that uses PCA for face feature extraction involves merging the features and reducing the dimensions that results in some information loss. To overcome ...

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with r...

Supervised feature extraction is used in data classification and, unlike unsupervised feature extraction, uses class labels to evaluate the quality of the extracted features. It can be computationally ineflcient to perform exhaustive searches to find optimal subsets of features. This article proposes an algorithm of supervised linear feature extraction based on the use of multivariate decision ...