In this paper, concept of possibility neutrosophic soft set and its operations are defined, and their properties are studied. An application of this theory in decision making is investigated. Also a similarity measure of two possibility neutrosophic soft sets is introduced and discussed. Finally an application of this similarity measure in personal selection for a firm.

This paper outlines a measure of language similarity based on structural similarity of surface syntactic dependency trees. Unlike the more traditional string-based measures, this measure tries to reflect “deeper” correspondences among languages. The development of this measure has been inspired by the experience from MT of syntactically similar languages. This experience shows that the lexical ...

This paper surveys the current best texture representations and studies their application for a texture similarity measure development. A simple experiment that evaluates texture similarity is proposed and the performance of several most advanced texture features is verified on it. In order to eliminate the influence of spectral information monospectral textures are considered in this study onl...

this study is an investigation of fuzzy linear regression model for crisp/fuzzy input and fuzzy output data. a least absolutes deviations approach to construct such a model is developed by introducing and applying a new metric on the space of fuzzy numbers. the proposed approach, which can deal with both symmetric and non-symmetric fuzzy observations, is compared with several existing models by...

This paper describes the work done as part of the shared task on Detecting Paraphrases in Indian Languages(DPIL) in Forum for Information Retrieval and Evaluation(FIRE 2016). Paraphrase identification is the task of deciding whether two given text fragments have the same meaning. Our detection system is for Malayalam language and makes use of the cosine similarity measure, an existing state of ...

It is vital to select an appropriate distance metric for many learning algorithm. Cosine distance is an efficient metric for measuring the similarity of descriptors in classification task. However, the cosine similarity metric learning (CSML)[1] is not widely used due to the complexity of its formulation and time consuming. In this paper, a Quasi Cosine Similarity Metric Learning (QCSML) is pro...

In this paper we introduce a new clustering algorithm for event detection in newspaper articles, which has two main features. Firstly, it makes use of the temporal references extracted from the document texts to define the document similarity function. Secondly, the algorithm works hierarchically. In the first level, documents with a high temporal-semantic similarity are grouped into individual...

The focus of this paper is the calculation of similarity between two concepts from an ontology for a Human-Like Interaction system. In order to facilitate this calculation, a similarity function is proposed based on five dimensions (sort, compositional, essential, restrictive and descriptive) constituting the structure of ontological knowledge. The paper includes a proposal for computing a simi...

Computing the semantic similarity between words is one of the key tasks in many language-based applications. Recent work has focused on using contextual clues for semantic similarity computation. In this paper, we propose a method to the measure semantic similarity between words using plain text contents. It takes into account information attributes (local) and topic information (global) of wor...

In this paper, we present a novel framework for analyzing video using self-similarity. Video scenes are located by analyzing inter-frame similarity matrices. The approach is flexible to the choice of similarity measure and is robust and data-independent because the data is used to model itself. We present the approach and its application to scene boundary detection. This is shown to dramaticall...