In decision making, similarity measure and distance between two objects are crucial to be able to determine the relationship between those objects. Many researchers have received much attention for their research on this subject. In this study, we propose two novel similarity measures between hesitant fuzzy linguistic term sets (HFLTSs). In addition, two extensions of Technique for Order of Pre...

We propose a novel similarity measure, called the correntropy coefficient, sensitive to higher order moments of the signal statistics based on a similarity function called the cross-correntopy. Cross-correntropy nonlinearly maps the original time series into a high-dimensional reproducing kernel Hilbert space (RKHS). The correntropy coefficient computes the cosine of the angle between the trans...

In this paper we propose a method termed as Face-Specific Subspace DCT Sign Only Product (FSS–DSOP), for face recognition. The proposed method is based on Face-Specific Subspace (FSS) technique using Discrete Cosine Transform (DCT) sign only product as similarity measure. The proposed approach aims to improve the recognition rate of the FSS technique under small size scenario with illumination ...

This paper introduces a new similarity measure, termed Binary Weighted Cosine (BWC) metric, for anomaly-based intrusion detection schemes that rely on using sequences of system calls. The new similarity measure considers both the number of shared system calls between two processes as well as frequencies of those calls. The k nearest neighbor (kNN) classifier is used to categorize a process as e...

Measuring the similarity between documents is an essential task in Document Clustering. This paper presents a new metric that is based on the number and the category of the Named Entities shared between news documents. Three different feature-weighting functions and two standard similarity measures were used to evaluate the quality of the proposed measure in multilingual news clustering. The re...

Clustering is a method which can be helpful in retrieval of relevant information from databases [9, 1]. Businesses use databases to gather information about completed transactions. Huge part of it has a linguistic form or categorical attributes, which do not have a natural order. Data in that form can be clustered by using of the measure of similarity [6]. Most of earlier work focused on form c...

Proper names are usually key to understanding the information contained in a document. Our work focuses on increasing the vocabulary coverage of a speech transcription system by automatically retrieving new proper names from contemporary diachronic text documents. The idea is to use in-vocabulary proper names as an anchor to collect new linked proper names from the diachronic corpus. Our assump...

Skin color is an important visual cue for computer vision systems involving human users. In this paper we combine skin color and optical flow for detection and tracking of skin regions. We apply these techniques to gesture recognition with encouraging results. We propose a novel skin similarity measure. For grouping detected skin regions we propose a novel skin region grouping mechanism. The pr...

Most CBIR systems use low-level visual features for representation and retrieval of images. Generally such methods suffer from the problems of high-dimensionality leading to more computational time and inefficient indexing and retrieval performance. This paper focuses on a low-dimensional color and shape based indexing technique for achieving efficient and effective retrieval performance. We pr...