Identification of New Parameters for Ontology Based Semantic Similarity Measures

Jain, Shivani and K.R, Seeja and Jindal, Rajni (2019) Identification of New Parameters for Ontology Based Semantic Similarity Measures. EAI Endorsed Transactions on Scalable Information Systems, 6 (20): e3. ISSN 2032-9407

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Abstract

A major challenge among various applications of computational linguistics, natural language processing and information retrieval is to measure semantic similarity accurately. In this research paper, various ontology-based approaches i.e. compute semantic similarity between words have been studied and listed their benefits and shortcomings on the various identified parameters. Earlier, correlation with human judgment was the single criteria for the judgment of good similarity measures. In this paper, more parameters for semantic similarity measures have been identified and a relative analysis of similarity measures is performed on the identified parameters. These identified parameters can be further utilized for formulating the new semantic similarity-measures in the latest research area of text mining, web mining and information retrieval. We have identified various parameters like features-set, applicability on various ontologies such as single ontology, cross ontology or fuzzy ontology, Ontology type, dataset applied and relationship mapping for the various measures. Through detailed analysis we have found that feature based and hybrid approaches has higher accuracy as compare to edge and content based methods and works in different type of ontologies. Recent research drawing interest to find new feature set in this area like fuzzy distance, graph generation and text snippets etc. Max Accuracy was achieved in single ontology 0.87 and 0.83 over cross ontologies. WordNet and MeSH are maximally utilized Global Ontologies.

Item Type: Article
Uncontrolled Keywords: Ontology, Natural-Language-Processing, Text-Mining, Knowledge-Based, Semantic-Similarity, WordNet
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 08 Oct 2020 13:57
Last Modified: 08 Oct 2020 13:57
URI: https://eprints.eudl.eu/id/eprint/714

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