Skip to main content

Two Stages Based Organization Name Disambiguity

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7181))

Abstract

With the rapid growth of user generated media, Twitter has become an important information resource where users share fresh information on any subject. Pursuing on the problem of finding related tweets to a given organization, we propose two stages based organization name disambiguity. Insufficient information and the diversity of organizations are two key problems for this task. We induce multiple types of features to enrich the information of organization to solve the problem of insufficient information. The relationships between tweets and organization, the relationships among tweets are mined in two stages to solve the diversity of organization. Furthermore, we probe the distribution of organization names’ ambiguity and its influence to different classifiers. Our experimental results on WePS-3 prove the proposed methods are effective and promising in performing this task.

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

Buying options

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. Amigó, E., Artiles, J., Gonzalo, J., Spina, D., Liu, B., Corujo, A.: WePS-3 Evaluation Campaign: Overview of the Online Reputation Management Task. In: 3rd Web People Search Evaluation Workshop (2010)

    Google Scholar 

  2. Yerva, S.R., Miklós, Z., Aberer, K.: It was Easy, when Apples and Blackberries were only Fruits. In: 3rd Web People Search Evaluation Workshop (2010)

    Google Scholar 

  3. Yoshida, M., Matsushima, S., Ono, S., Sato, I., Nakagawa, H.: ITC-UT: Tweet Categorization by Query Categorization for On-line Reputation Management. In: 3rd Web People Search Evaluation Workshop (2010)

    Google Scholar 

  4. Kalmar, P.: Bootstrapping Websites for Classification of Organization Names on Twitter. In: 3rd Web People Search Evaluation Workshop (2010)

    Google Scholar 

  5. García-Cumbreras, M.A., García-Vega, M., Martínez-Santiago, F., Peréa-Ortega, J.M.: SINAI at WePS-3: Online Reputation Management. In: 3rd Web People Search Evaluation Workshop (2010)

    Google Scholar 

  6. Perez-Tellez, F., Pinto, D., Cardiff, J., Rosso, P.: On the Difficulty of Clustering Microblog Texts for Online Reputation Management. In: 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis, ACL-HLT (2011)

    Google Scholar 

  7. Dan, O., Feng, J., Davision, B.D.: A Bootstrapping Approach to Identifying Relevant Tweets for Social TV. In: 5th International AAAI Conference Weblogs and Social Media (2011)

    Google Scholar 

  8. Zhou, G.D., Kong, F.: Global Learning of Noun Phrase Anaphoricity in Coreference Resolution via Label Propagation. In: Empirical Methods in Natural Language Processing, pp. 978–986 (2009)

    Google Scholar 

  9. Niu, Z.Y., Ji, D.H., Tan, C.T.: Word Sense Disambiguation Using Label Propagation Based Semi-Supervised Learning. In: 43rd Annual Meeting on Association for Computational Linguistics, pp. 395–402 (2005)

    Google Scholar 

  10. Chen, J.X., Ji, D.H., Tan, C.T., Niu, Z.Y.: Relation Extraction Using Label Propagation Based Semi-supervised Learning. In: 21st International Conference on Computational Linguistics and 44th Annual Meeting on Association for Computational Linguistics, pp. 129–136 (2006)

    Google Scholar 

  11. Zhu, X., Ghahramani, Z.: Learning from Labeled and Unlabeled Data with Label Propagation. Technical Report CMU-CALD-02-107, Carnegie Mellon University (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zhang, S., Wu, J., Zheng, D., Meng, Y., Xia, Y., Yu, H. (2012). Two Stages Based Organization Name Disambiguity. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2012. Lecture Notes in Computer Science, vol 7181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28604-9_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28604-9_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28603-2

  • Online ISBN: 978-3-642-28604-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics