Towards Classification of Web ontologies using the Horizontal and Vertical Segmentation

TL;DR

This paper explores methods for segmenting large web ontologies into smaller, manageable parts using horizontal and vertical segmentation techniques to improve their usability and reasoning efficiency.

Contribution

It introduces a segmentation approach that extracts meaningful ontology segments representing layers or generations, enhancing the handling of large ontologies.

Findings

Segmentation improves ontology manageability.

Extracted segments are valid ontologies.

Method facilitates reasoning on large ontologies.

Abstract

The new era of the Web is known as the semantic Web or the Web of data. The semantic Web depends on ontologies that are seen as one of its pillars. The bigger these ontologies, the greater their exploitation. However, when these ontologies become too big other problems may appear, such as the complexity to charge big files in memory, the time it needs to download such files and especially the time it needs to make reasoning on them. We discuss in this paper approaches for segmenting such big Web ontologies as well as its usefulness. The segmentation method extracts from an existing ontology a segment that represents a layer or a generation in the existing ontology; i.e. a horizontally extraction. The extracted segment should be itself an ontology.