Wu and Weld WWW 2008

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Citation

Wu, F. and Weld, D. 2008. Automatically Refining the Wikipedia Infobox Ontology. In Proceedings of the 17th Conference of the World Wide Web, pp. 635-644, ACM, New York.

Online version

University of Washington

Summary

This is a paper that introduces an autonomous system for refining Wikipedia’s infobox information schema to create a cleanly-structured ontology. Advanced query capability, improved information extractors and semiautomatic generation of new infobox templates are shown as advantages of a refined ontology. The ontology refinement problem is solved using both Support Vector Machines and a more powerful joint-inference approach expressed in Markov Logic Networks.

The autonomous system, presented as Kylin Ontology Generator (KOG), is comprised of three modules:

  • a schema cleaner, which merges duplicate classes and attributes and prunes rarely-used ones;
  • a subsumption detector, which identifies is-a relations between infobox classes (e.g. "volleyball player" is-a "athlete");
  • and a schema mapper, which builds attribute mappings between related infobox classes.

The subsumption detection task is modeled as a binary classification problem and several intuitive indicators are used as features to train the classifiers:

  • similarity measure: the similarity between two infobox classes, measured using the TF/IDF scores between bags of words taken from their attribute set, the first sentence of each of their instances and their category tags.

Experimental result

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Related papers

This paper is based on Wu and Weld CIKM 2007.