A Review on Computing Semantic Similarity of Concepts in Knowledge Graphs

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Harshal Wanjari, Prof. Nutan Dhande

Abstract

Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between them is based on the likeness of their meaning or semantic content as opposed to similarity which can be estimated regarding their syntactical representation (e.g. their string format). One of the drawbacks of conventional knowledge-based approaches (e.g. path or lch) in addressing such task is that the semantic similarity of any two concepts with the same path length is the same (uniform distance problem).To propose a weighted path length (wpath) method to combine both path length and IC in measuring the semantic similarity between concepts. The IC of two concepts� LCS is used to weight their shortest path length so that those concept pairs having same path length can have different semantic similarity score if they have different LCS.

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How to Cite
, H. W. P. N. D. (2018). A Review on Computing Semantic Similarity of Concepts in Knowledge Graphs. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(1), 419–423. Retrieved from http://www.ijfrcsce.org/index.php/ijfrcsce/article/view/1033
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