We present a description of the system submitted to the Semantic Textual Similarity (STS) shared task at SemEval 2016. The task is to assess the degree to which two sentences carry the same meaning. We have designed two different methods to automatically compute a similarity score between sentences. The first method combines a variety of semantic similarity measures as features in a machine lea...

We extend the results obtained for different cases of the product superposition of periodic functions, and the determination of the scattered fields, for the case of circular symmetry. The characteristics of focalization for such cases are studied. We name Cantor-Fresnel zone plate the structures obtained with this method. Also, in this study can be included the focalization by periodic, Cantor...

How similar are two corpora? A measure of corpus similarity would be very useful for NLP for many purposes, such as estimating the work involved in porting a system from one domain to another. First, we discuss difficulties in identifying what we mean by 'corpus similariti: human similarity judgements are not finegrained enough, corpus similarity is inherently multidimensional, and similarity c...

Life service information plays an important role in people’s life, such as weather conditions, so the study of how to get life service information has important significance. This paper put forward a question processing method called “integrated semantic algorithm” in Q&A System of life service information. The new algorithm was based on the semantic web, word order similarity algorithm and the...

In this paper, we define a rough cosine similarity measure between two rough neutrosophic sets. The notions of rough neutrosophic sets (RNS) will be used as vector representations in 3D-vector space. The rating of all elements in RNS is expressed with the upper and lower approximation operator and the pair of neutrosophic sets which are characterized by truth-membership degree, indeterminacy-me...

We present a new iterative algorithm for ontology mapping where we combine standard string distance metrics with a structural similarity measure that is based on a vector representation. After all pairwise similarities between concepts have been calculated we apply well-known graph algorithms to obtain an optimal matching. Our algorithm is also capable of using existing mappings to a third onto...

Keeping in consideration the high demand for clustering, this paper focuses on understanding and implementing K-means clustering using two different similarity measures. We have tried to cluster the documents using two different measures rather than clustering it with Euclidean distance. Also a comparison is drawn based on accuracy of clustering between fuzzy and cosine similarity measure. The ...

Let G be a group. Recall that the intersection graph of subgroups of G is an undirected graph whose vertex set is the set of all nontrivial subgroups of G and distinct vertices H,K are joined by an edge in this graph if and only if the intersection of H and K is nontrivial. The aim of this article is to investigate the interplay between the group-theoretic properties of a finite group G and the...

As WWW grows at an increasing speed, a classifier targeted at hypertext has become in high demand. While document categorization is quite a mature, the issue of utilizing hypertext structure and hyperlinks has been relatively unexplored. In this paper, we introduce tensor space model for representing hypertext documents. We exploit the local-structure and neighborhood recommendation encapsulate...