Deep Neural Networks for Matching Online Social Networking Profiles

  • Vicentiu-Marian Ciorbaru
  • Traian RebedeaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10448)


This paper details a novel method for grouping together online social networking profiles of the same person extracted from different sources. Name ambiguity arises naturally in any culture due to the popularity of specific names which are shared by a large number of people. This is one of the main problems in people search, which is also multiplied by the number of different data sources that contain information about the same person. Grouping pages from various social networking websites in order to disambiguate between different individuals with the same name is an important task in people search. This allows building a detailed description and a consolidated online identity for each individual. Our results show that given a large enough dataset, neural networks and word embeddings provide the best method to solve this problem.


Profile matching Social networking Deduplication Deep learning 


  1. 1.
    Artiles, J., Borthwick, A., Gonzalo, J., Sekine, S., Amigó, E.: Weps-3 evaluation campaign: overview of the Web people search clustering and attribute extraction tasks. In: CLEF (Notebook Papers/LABs/Workshops) (2010)Google Scholar
  2. 2.
    Artiles, J., Gonzalo, J., Sekine, S.: Weps 2 evaluation campaign: overview of the web people search clustering task. In: 18th WWW Conference 2nd Web People Search Evaluation Workshop (WePS 2009), vol. 9. Citeseer (2009)Google Scholar
  3. 3.
    Artiles, J., Gonzalo, J., Verdejo, F.: A testbed for people searching strategies in the www. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 569–570. ACM (2005)Google Scholar
  4. 4.
    Chen, Y., Lee, S.Y.M., Huang, C.R.: Polyuhk: A robust information extraction system for web personal names. In: 18th WWW Conference 2nd Web People Search Evaluation Workshop (WePS 2009) (2009)Google Scholar
  5. 5.
    Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, pp. 3111–3119 (2013)Google Scholar
  6. 6.
    Morris, M.R., Teevan, J., Panovich, K.: What do people ask their social networks, and why? a survey study of status message q&a behavior. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 1739–1748. ACM (2010)Google Scholar
  7. 7.
    Nair, V., Hinton, G.E.: Rectified linear units improve restricted boltzmann machines. In: Proceedings of the 27th International Conference on Machine Learning (ICML-10), pp. 807–814 (2010)Google Scholar
  8. 8.
    Nuray-Turan, R., Chen, Z., Kalashnikov, D.V., Mehrotra, S.: Exploiting web querying for web people search in weps2. In: 18th WWW Conference 2nd Web People Search Evaluation Workshop (WePS 2009). Citeseer (2009)Google Scholar
  9. 9.
    Perito, D., Castelluccia, C., Kaafar, M.A., Manils, P.: How unique and traceable are usernames? In: Proceedings of the 11th International Conference on Privacy Enhancing Technologies, PETS 2011, pp. 1–17 (2011). Scholar
  10. 10.
    Srivastava, N., Hinton, G.E., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929–1958 (2014)MathSciNetzbMATHGoogle Scholar
  11. 11.
    Sullivan, D.: Google now handles at least 2 trillion searches per year (2016). Accessed 10 Apr 2017
  12. 12.
    Watts, D.J., Dodds, P.S., Newman, M.E.: Identity and search in social networks. Science 296(5571), 1302–1305 (2002)CrossRefGoogle Scholar
  13. 13.
    Zhang, Y., Tang, J., Yang, Z., Pei, J., Yu, P.S.: Cosnet: connecting heterogeneous social networks with local and global consistency. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2015, NY, USA, pp. 1485–1494 (2015).

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University Politehnica of BucharestBucharestRomania

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