Extending GWAPs for Building Profile Aware Associative Networks

  • Abdelraouf Hecham
  • Madalina CroitoruEmail author
  • Pierre Bisquert
  • Patrice Buche
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9717)


Associative networks have been long used as a way to provide intelligent machines with a working memory and applied in various domains such as Natural Language Processing or customer associations analysis. While giving out numerous practical advantages, existing Games With a Purpose (GWAPs) for eliciting associative networks cannot be employed in certain domains (for example in customer associations analysis) due to the lack of profile based filtering. In this paper we ask the following research question: “Does considering agents profile information when constructing an associative network by a game with a purpose allows to extract subjective information that might have been lost otherwise?”. In order to answer this question we present the KAT (Knowledge AcquisiTion) game that extends upon the state of the art by considering agent profiling. We formalise the game, implement it and carry out a pilot study that validates the above mentioned research hypothesis.



The authors acknowledge the support of ANS1 1208 IATE INCOM INRA grant, ANR grants ASPIQ (ANR-12- BS02-0003), QUALINCA (ANR-12-0012) and DUR-DUR (ANR-13-ALID-0002). The work of the second author has been carried out part of the research delegation at INRA MISTEA Montpellier and INRA IATE CEPIA Axe 5 Montpellier. The authors are grateful to DUR-DUR participants and IUT AS students for the help with the experimentation.


  1. 1.
    Baader, F.: The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  2. 2.
    Bisquert, P., Croitoru, M., Dupin de Saint-Cyr, F.: Four ways to evaluate arguments according to agent engagement. In: Guo, Y., Friston, K., Aldo, F., Hill, S., Peng, H. (eds.) BIH 2015. LNCS, vol. 9250, pp. 445–456. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  3. 3.
    Bisquert, P., Croitoru, M., de Saint-Cyr, F.D.: Towards a dual process cognitive model for argument evaluation. In: Beierle, C., Dekhtyar, A. (eds.) SUM 2015. LNCS, vol. 9310, pp. 298–313. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  4. 4.
    Brachman, R.J., Schmolze, J.G.: An overview of the KL-ONE knowledge representation system. Cogn. Sci. 9(2), 171–216 (1985)CrossRefGoogle Scholar
  5. 5.
    Cambria, E., Rajagopal, D., Kwok, K., Sepulveda, J.: Gecka: game engine for commonsense knowledge acquisition. In: The Twenty-Eighth International Flairs Conference (2015)Google Scholar
  6. 6.
    Chan, K.T., King, I., Yuen, M.-C.: Mathematical modeling of social games. In: International Conference on Computational Science and Engineering, CSE 2009, vol. 4, pp. 1205–1210. IEEE (2009)Google Scholar
  7. 7.
    Findler, N.V.: Associative Networks: Representation and Use of Knowledge by Computers. Academic Press, New York (2014)zbMATHGoogle Scholar
  8. 8.
    Fry, H.: The Mathematics of Love: Patterns, Proofs, and the Search for the Ultimate Equation. Simon and Schuster, New York (2015)Google Scholar
  9. 9.
    Greenwood, P.E., Nikulin, M.S.: A Guide to Chi-Squared Testing, vol. 280. Wiley, New York (1996)zbMATHGoogle Scholar
  10. 10.
    Henderson, G.R., Iacobucci, D., Calder, B.J.: Brand diagnostics: mapping branding effects using consumer associative networks. Eur. J. Oper. Res. 111(2), 306–327 (1998)CrossRefzbMATHGoogle Scholar
  11. 11.
    Lafourcade, M.: Making people play for lexical acquisition with the JeuxDeMots prototype. In: 7th International Symposium on Natural Language Processing, SNLP 2007, p. 7 (2007)Google Scholar
  12. 12.
    Markotschi, T., Völker, J.: Guesswhat?!-Human intelligence for mining linked data (2010)Google Scholar
  13. 13.
    Miller, G.A.: Wordnet: a lexical database for english. Commun. ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  14. 14.
    Quillan, M.R.: Semantic memory. Technical report, DTIC Document (1966)Google Scholar
  15. 15.
    Siorpaes, K., Hepp, M.: Games with a purpose for the semantic web. IEEE Intell. Syst. 3, 50–60 (2008)CrossRefGoogle Scholar
  16. 16.
    Sowa, J.F.: Conceptual graphs for a data base interface. IBM J. Res. Dev. 20(4), 336–357 (1976)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Teichert, T.A., Schöntag, K.: Exploring consumer knowledge structures using associative network analysis. Psychol. Mark. 27(4), 369–398 (2010)CrossRefGoogle Scholar
  18. 18.
    Thaler, S., Simperl, E.P.B., Siorpaes, K.: SpotTheLink: a game for ontology alignment. Wissensmanagement 182, 246–253 (2011)Google Scholar
  19. 19.
    Vannella, D., Jurgens, D., Scarfini, D., Toscani, D., Navigli, R.: Validating and extending semantic knowledge bases using video games with a purpose. ACL 1, 1294–1304 (2014)Google Scholar
  20. 20.
    Von Ahn, L.: Games with a purpose. Computer 39(6), 92–94 (2006)CrossRefGoogle Scholar
  21. 21.
    Von Ahn, L., Dabbish, L.: Designing games with a purpose. Commun. ACM 51(8), 58–67 (2008)Google Scholar
  22. 22.
    Von Ahn, L., Kedia, M., Blum, M.: Verbosity: a game for collecting common-sense facts. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 75–78. ACM (2006)Google Scholar
  23. 23.
    West, R., Pineau, J., Precup, D.: Wikispeedia: an online game for inferring semantic distances between concepts. In: IJCAI, pp. 1598–1603 (2009)Google Scholar
  24. 24.
    Wilson, J.R., Sharples, S.: Evaluation of Human Work. CRC Press, London (2015)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Abdelraouf Hecham
    • 1
  • Madalina Croitoru
    • 1
    Email author
  • Pierre Bisquert
    • 2
  • Patrice Buche
    • 2
  1. 1.GraphIK, LIRMM, University of MontpellierMontpellierFrance
  2. 2.GraphIK, IATE, INRAMontpellierFrance

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