A Sentence Similarity Measure Based on Conceptual Elements
Keywords:
Sentence Similarity Measure, Concept, FrameNet,Abstract
There has always been a growing interest in sentence similarity measure for practical NLP tasks using various state-of-art NLP methods. Some of the widely used methods in measuring sentence similarity are lexical semantics, deep learning, neural networks, ontology, statistical models, graph based model and etc. Based on our findings, one of the main drawbacks in using these methods is not able to resolve word ambiguity where one word can have different interpretations in different sentences. In this paper, we present a sentence similarity measure by representing the sentences in conceptual elements to measure the semantic similarity between sentences. We used Microsoft Paraphrase Corpus (MSR) and Quora question pairs dataset to evaluate the performance. The study concludes that we were able to use conceptual elements to measure sentence similarity with the highest micro averaged precision of 0.71.Downloads
Published
How to Cite
Issue
Section
License
TRANSFER OF COPYRIGHT AGREEMENT
The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):
- All proprietary right other than copyright, such as patent rights
- The right to make further copies of all or part of the published article for my use in classroom teaching
- The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
- The right to make copies of the published work for internal distribution within the institution that employs me
I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.
