Ontologies derived from Wikipedia (original) (raw)

Wikipedia-based Extraction of Lightweight Ontologies for Concept Level Annotation

This poster describes a project under development in which we propose a framework for automating the development of lightweight ontologies for semantic annotations. When considering building ontologies for annotations in any domain, we follow the process of ontology learning in Stelios 2006, but since we are looking for lightweight ontology, we only consider a subset of these tasks, which are the acquisition of domain terminologies, generating concept hierarchies, learning relations and properties, and ontology evaluation. When developing the framework modules we rely in most of our knowledge base on the structure of the Wikipedia, which is the category and the link structure of the Wikipedia pages in addition to specific sections of the content. To ensure machine understandability and interoperability, ontologies have to be explicit to make an annotation publicly accessible, formal to make an annotation publicly agreeable, and unambiguous to make an annotation publicly identifiable...

A resource-poor approach for linking ontology classes to Wikipedia articles

2008

Abstract The applicability of ontologies for natural language processing depends on the ability to link ontological concepts and relations to their realisations in texts. We present a general, resource-poor account to create such a linking automatically by extracting Wikipedia articles corresponding to ontology classes. We evaluate our approach in an experiment with the Music Ontology. We consider linking as a promising starting point for subsequent steps of information extraction.

Wikipedia as an ontology for describing documents

Proceedings of the Second International Conference on Weblogs and Social Media, 2008

Identifying topics and concepts associated with a set of documents is a task common to many applications. It can help in the annotation and categorization of documents and be used to model a person's current interests for improving search results, business intelligence or selecting appropriate advertisements. One approach is to associate a document with a set of topics selected from a fixed ontology or vocabulary of terms. We have investigated using Wikipedia's articles and associated pages as a topic ontology for this ...