A Comprehensive Survey of Ontology Summarization: Measures and Methods

TL;DR

This survey reviews various measures and methods for ontology summarization, highlighting the importance of effective summarization techniques to improve understanding of complex ontologies in the Semantic Web.

Contribution

It provides a comprehensive overview of current metrics and approaches used in ontology summarization, consolidating state-of-the-art practices.

Findings

Various measures are used for ontology summarization.

Current approaches focus on different metrics for effective summaries.

Ontology summarization enhances understanding of complex semantic structures.

Abstract

The Semantic Web is becoming a large scale framework that enables data to be published, shared, and reused in the form of ontologies. The ontology which is considered as basic building block of semantic web consists of two layers including data and schema layer. With the current exponential development of ontologies in both data size and complexity of schemas, ontology understanding which is playing an important role in different tasks such as ontology engineering, ontology learning, etc., is becoming more difficult. Ontology summarization as a way to distill knowledge from an ontology and generate an abridge version to facilitate a better understanding is getting more attention recently. There are various approaches available for ontology summarization which are focusing on different measures in order to produce a proper summary for a given ontology. In this paper, we mainly focus on the common metrics which are using for ontology summarization and meet the state-of-the-art in ontology summarization.