Enriching very large ontologies using the WWW

By Eneko Agirre, Olatz Ansa, Eduard H. Hovy, David Martínez. 2000

380 citations recorded by the source corpus.

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.

Subfields: Artificial Intelligence

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Citations in the corpus

On the Use of Automatically Acquired Examples for All-Nouns Word Sense Disambiguation (2008, methodology): “Previous work (Agirre & Martinez, 2000) has reported that the distribution of the number of examples per word sense (prior for short) has a strong inﬂuence in the quality of the results.”
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing (2012, background): “Some approaches have been directly targeting to enrich existing resources, as we do here with WordNet, (Agirre et al., 2000; Cuadros and Rigau, 2008; Cimiano, 2006) but these never use learning.”
Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis (2005, background): “Agirre, Ansa, Hovy, and Martinez (2000), download related texts from the Web to enrich a given ontology.”
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites (2004, methodology): “The majority of papers in this area propose methods for extending an existing ontology with unknown words (e.g., Agirre et al. 2000 and Alfonseca and Manandhar 2002).”
Towards the self-annotating web (2004, background): “• Others use the Web to cope with data sparseness problems in tasks that require statistics about possible semantic relationships ([1, 14, 21, 23]).”
Introduction to the Special Issue on the Web as Corpus (2003, background): “Arguments raged, and it was not clear whether corpus work was an acceptable 2.1 Some Current Themes Since then there have been many papers, at ACL and elsewhere, and we can mention only a few.”