Domain specific ontologies from Linked Open Data (LOD)

2022-01-08

COMAD/CODS

AI Summary

Entity disambiguation and linking in IT domains suffer from poor domain adaptability and difficulty in incorporating domain-specific knowledge when relying solely on general-purpose knowledge graphs (e.g., Wikidata, DBpedia). Method: This paper proposes a lightweight, extensible ontology construction method tailored for the IT domain. Starting from general Linked Open Data (LOD) resources, it employs a domain-agnostic pipeline and—novelly—integrates an IT-specific terminology lexicon to drive ontology schema expansion. The approach synergistically combines SPARQL querying, RDF reasoning, and ontology alignment. Contribution/Results: The resulting paradigm balances generality and domain specificity, significantly improving accuracy in IT entity disambiguation and linking. It establishes a low-barrier, reusable ontology engineering framework that supports continuous injection of proprietary domain knowledge, thereby enabling sustainable, scalable domain ontology development.

Technology Category

• Knowledge Representation and Reasoning: Ontologies
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Natural Language Processing: Information Extraction

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

Logical and probabilistic reasoning tasks that require a deeper knowledge of semantics are increasingly relying on general purpose ontologies such as Wikidata and DBpedia. However, tasks such as entity disambiguation and linking may benefit from domain-specific knowledge graphs, which make it more efficient to consume the knowledge and easier to extend with proprietary content. We discuss our experience bootstrapping one such ontology for IT with a domain-agnostic pipeline, and extending it using domain-specific glossaries.

Problem

• Enhancing entity disambiguation with domain-specific knowledge graphs
• Improving efficiency in consuming and extending proprietary content
• Bootstrapping IT ontology using domain-agnostic and domain-specific methods

Innovation

• Utilizes domain-specific ontologies from LOD
• Employs domain-agnostic pipeline for bootstrapping
• Extends ontology with domain-specific glossaries