Enriching very large ontologies using the WWW

Abstract

This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW related to a concept is described. These document collections are used 1) to construct topic signatures (lists of topically related words) for each concept in WordNet, and 2) to build hierarchical clusters of the concepts (the word senses) that lexicalize a given word. The overall goal is to overcome two shortcomings of WordNet: the lack of topical links among concepts, and the proliferation of senses. Topic signatures are validated on a word sense disambiguation task with good results, which are improved when the hierarchical clusters are used.

6 pages

Cited by in corpus (4)

• Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis
• Exploring automatic word sense disambiguation with decision lists and the Web
• Towards Open-Text Semantic Parsing via Multi-Task Learning of Structured Embeddings
• ConTrOn: Continuously Trained Ontology based on Technical Data Sheets and Wikidata