Similarity method is the key of the user-based collaborative filtering recommend algorithm. The traditional similarity measures, which cosine similarity, adjusted cosine similarity and Pearson correlation similarity are included, have some advantages such as simple, easy and fast, but with the sparse dataset they may lead to bad recommendation quality. In this article, we first research how the...

In this paper, we define a new cosine similarity between two interval valued neutrosophic sets based on Bhattacharya’s distance [19]. The notions of interval valued neutrosophic sets (IVNS, for short) will be used as vector representations in 3D-vector space. Based on the comparative analysis of the existing similarity measures for IVNS, we find that our proposed similarity measure is better an...

Measuring text similarity has been studied for a long time due to its importance in many applications in natural language processing and related areas such as Web-based document searching. One such possible application which is investigated in this paper is determining the similarity between course descriptions of the same subject for credit transfer among various universities or similar academ...

In a previous article (Rahman, Guns, Rousseau, and Engels, 2015) we described several approaches to determine the cognitive distance between two units. One of these approaches was based on what we called barycenters in N dimensions. The present note corrects this terminology and introduces the more adequate term ‘similarity-adapted publication vectors’. Furthermore, we correct an error in norma...

In this proof-of-concept study we use standard cosine similarity measure to calculate the semantic similarity between two pieces of text – the citing document and the cited text. Three subject matter experts then evaluate the citing and the cited text based on the cosine score to give their judgement on the semantic similarity between the two pieces of text.

Objective: In pattern recognition and medical diagnosis, similarity measure is an important mathematical tool. To overcome some disadvantages of existing cosine similarity measures of simplified neutrosophic sets (SNSs) in vector space, this paper proposed improved cosine similarity measures of SNSs based on cosine function, including single valued neutrosophic cosine similarity measures and in...

When dealing with document similarity many methods exist today, like cosine similarity. More complex methods are also available based on the semantic analysis of textual information, which are computationally expensive and rarely used in the real time feeding of content as in enterprisewide search environments. To address these real-time constraints, we developed a new measure of document simil...

This article presents a distance and angle similarity measure. The integrated similarity measure takes the strengths of both the distance and direction of measured documents into account. This article analyzes the features of the similarity measure by comparing it with the traditional distance-based similarity measure and the cosine measure, providing the iso-similarity contour, investigating t...

The objective of the study is to present cosine similarity measure based multi-attribute decision making under neutrosophic environment. The assesments of alternatives over the attributes are expressed with trapezoidal fuzzy neutrosophic numbers in which the three independent components namely, truth-membership degree (T), indeterminacy-membership degree (I) and falsity-membership degree (F) ar...