Social Relationships as a Means for Identifying an Individual in Large Information Spaces

  • Katarína Kostková
  • Michal Barla
  • Mária Bieliková
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 331)


In this paper we describe a method for identification of a particular user in large information spaces such as the Web is. Our main goal is to be able to decide whether the particular information found on the Web is relevant to the person being looked-up or not by taking into account additional background knowledge about that person: his or her social network. Our method combines semantically as well as syntactically based metrics to compare different social networks acquired during the identification process. We describe evaluation of the proposed method and its comparison to the related works.


disambiguation individual identification social network social networks comparison background knowledge 


  1. 1.
    Barla, M., et al.: Rule-based User Characteristics Acquisition from Logs with Semantics for Personalized Web-based Systems. Computing & Informatics 28(4), 399–427 (2009)Google Scholar
  2. 2.
    Bollegala, D., et al.: Disambiguating Personal Names on the Web Using Automatically Extracted Key Phrases. In: ECAI 2006, pp. 553–557. IOS Press, Amsterdam (2006)Google Scholar
  3. 3.
    Driscoll, P., Yarowsky, D.: Disambiguation of Standardized Personal Name Variants (2007), (17.05.2010)
  4. 4.
    Han, X., Zhao, J.: Web personal name disambiguation based on reference entity tables mined from the web. In: Proc. of the 11th Int. Workshop on Web information and Data Management, WIDM 2009, Hong Kong, China, pp. 75–82. ACM, New York (2009)Google Scholar
  5. 5.
    Laclavík, M., et al.: Ontea: Platform for Pattern Based Automated Semantic Annotation. Computing and Informatics 28(4), 555–579 (2009)Google Scholar
  6. 6.
    Malin, B.: Unsupervised Name Disambiguation via Social Network Similarity. In: Workshop on Link Analysis, Counterterrorism, and Security (2005)Google Scholar
  7. 7.
    Mann, G.S., Yarowsky, D.: Unsupervised Personal Name Disambiguation. In: Natural Language Learning Workshop at HLT-NAACL 2003, Association for Computational Linguistics, pp. 33–40 (2003)Google Scholar
  8. 8.
    Návrat, P., Taraba, T., Bou Ezzeddine, A., Chudá, D.: Context Search Enhanced by Readability Index. In: Artificial Intelligence in Theory and Practice. IFIP WCC. IFIP Series, vol. 276, pp. 373–382. Springer Science+Business Media, LLC, New York (2008)Google Scholar
  9. 9.
    On, B., Lee, D., Kang, J., Mitra, P.: Comparative study of name disambiguation problem using a scalable blocking-based framework. In: Proc. of the 5th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2005, pp. 344–353. ACM, New York (2005)Google Scholar
  10. 10.
    Omelina, Ľ.: Extracting Information from Web Pages Based on Graph Models. In: Bieliková, M. (ed.) IIT.SRC 2009: Proc. of Student Research Conference, STU Bratislava, pp. 105–112 (2009)Google Scholar
  11. 11.
    Reuther, P.: Personal Name Matching: New Test Collections and a Social Network based Approach. University of Trier, Mathematics/Computer Science: Tech. Report 06-01 (2006)Google Scholar
  12. 12.
    Reuther, P., et al.: Managing the Quality of Person Names in DBLP. In: Gonzalo, J., Thanos, C., Verdejo, M.F., Carrasco, R.C. (eds.) ECDL 2006. LNCS, vol. 4172, pp. 508–511. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Wan, X., Gao, J., Li, M., Ding, B.: Person resolution in person search results: WebHawk. In: Proc. of the 14th ACM Int. Conf. on Information and Knowledge Management, CIKM 2005, Bremen, Germany, pp. 163–170. ACM, New York (2005)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2010

Authors and Affiliations

  • Katarína Kostková
    • 1
  • Michal Barla
    • 1
  • Mária Bieliková
    • 1
  1. 1.Faculty of Informatics and Information TechnologiesSlovak University of TechnologyBratislavaSlovakia

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