Skip to main content
SpringerLink
Log in
Book cover

Advances on Digital Television and Wireless Multimedia Communications pp 299–306Cite as

A Review of Information Content Metric for Semantic Similarity

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 331))

Abstract

All along, Information Content (IC) of concept is a hot topic. It is an important dimension of accessing semantic similarity between two concepts or word senses. Much work has been done. This paper illustrated the use of IC in semantic similarity computing and then focuses on IC metric. It reviews and analyses Corpora-dependent and Corpora-independent IC approach. Hyponym-based, Leaves-based and Relation-based IC Metric is presented respectively. The important related issues are highlighted. Finally further research is outlined for the improvement of IC.

The work in the paper was supported by Shanghai Scientific Development Foundation (Grant No. 11530700300) and Shandong Excellent Young Scientist Award Fund (Grant No. BS2010DX012).

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Formica, A.: Concept similarity in formal concept analysis: an information content approach. Knowl. -Based Syst. 21(1), 80–87 (2007)

    Article  MathSciNet  Google Scholar 

  2. Jiang, J.J., Conrath, D.W.: Semantic similarity based on corpus statistics and lexical taxonomy. In: Proceedings of International Conference on Research in Computational Linguistics, Taiwan, pp. 19–33 (1997)

    Google Scholar 

  3. Lin, D.: An information-theoretic definition of similarity. In: Proceedings of the 15th International Conference on Machine Learning, Madison, Wisconsin, pp. 296–304 (1998)

    Google Scholar 

  4. Pirró, G.: A semantic similarity metric combining features and intrinsic information content. Data Knowl. Eng. 68(11), 1289–1308 (2009)

    Article  Google Scholar 

  5. Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, Montréal, Québec, pp. 448–453 (1995)

    Google Scholar 

  6. Seco, N., Veale, T., Hayes, J.: An intrinsic information content metric for semantic similarity in WordNet. In: Proceedings of the 16th European Conference on Artificial Intelligence, Valencia, Spain, pp. 1089–1090 (2004)

    Google Scholar 

  7. Zhou, Z., Wang, Y., Gu, J.: A new model of information content for semantic similarity in WordNet. In: Proceedings of Second International Conference on Future Generation Communication and Networking Symposia, China, pp. 85–89 (2008)

    Google Scholar 

  8. Sánchez, D., Batet, M., Isern, D.: Ontology-based information content computation. Knowl. -Based Syst. 24, 297–303 (2011)

    Article  Google Scholar 

  9. Seddiqui, H., Aono, M.: Metric of intrinsic information content for measuring semantic similarity in an ontology. In: Proceedings of 7th Asia-Pacific Conference on Conceptual Modeling, Australia, pp. 89–96 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science and Technology Department, Department of Educational Information Technology, East China Normal University, Shanghai, 200062, China

    Lingling Meng

  2. Computer Science and Technology Department, East China Normal Universtiy, Shanghai, 200062, China

    Junzhong Gu

  3. College of Physics and Engineering, Qufu Normal University, Qufu, 273165, China

    Zili Zhou

Authors
  1. Lingling Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Junzhong Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zili Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Image Communication and Information Processing, Shanghai Jiao Tong University, 800 Dongchuan Road, 200240, Shanghai, P. R. China

    Wenjun Zhang  & Xiaokang Yang  & 

  2. School of Communication and Information Engineering, Shanghai University, 99 Shangda Road, 200444, Shanghai, P. R. China

    Zhixiang Xu  & Ping An  & 

  3. School of Computer Science, Fudan University, 220 Handan Road, 200433, Shanghai, P. R. China

    Qizhen Liu

  4. Department of Computer Science and Technology, East China Normal University, 500 Dongchuan Road, 200241, Shanghai, P. R. China

    Yue Lu

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Meng, L., Gu, J., Zhou, Z. (2012). A Review of Information Content Metric for Semantic Similarity. In: Zhang, W., Yang, X., Xu, Z., An, P., Liu, Q., Lu, Y. (eds) Advances on Digital Television and Wireless Multimedia Communications. Communications in Computer and Information Science, vol 331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34595-1_42

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34595-1_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34594-4

  • Online ISBN: 978-3-642-34595-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation