Towards an enhanced and adaptable ontology by distilling and assembling online encyclopedias

  • Authors:
  • Shan Jiang;Lidong Bing;Yan Zhang

  • Affiliations:
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA;The Chinese University of Hong Kong, Hong Kong, China;Peking University, Beijing, China

  • Venue:
  • Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
  • Year:
  • 2013

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Abstract

In this paper, we investigate the problem of making better use of semantic knowledge obtained from different encyclopedia sources. We propose a framework to integrate different encyclopedias and reorganize the information. We also utilize Learning to Rank models to distill out more functional knowledge from the encyclopedic information and then align the knowledge with a WordNet-like ontology. Finally as a demonstration, a Chinese semantic knowledge repository named JNet is constructed based on this framework. Experiments show that the proposed methods work well and the three steps reinforce each other towards a more powerful ontology.