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Ways to Develop Human-Level Web Intelligence: A Brain Informatics Perspective

  • Ning Zhong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4519)

Abstract

In this paper, we briefly investigate several ways to develop human-level Web intelligence (WI) from a brain informatics (BI) perspective. BI can be regarded as brain sciences in WI centric IT age and emphasizes on a systematic approach for investigating human information processing mechanism. The recently designed instrumentation (fMRI etc.) and advanced IT are causing an impending revolution in both WI and BI, making it possible for us to understand intelligence in depth and develop human-level Web intelligence.

Keywords

Human Intelligence Human Information Processing Social Intelligence Granular Computing Brain Science 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284, 34–43 (2001)CrossRefGoogle Scholar
  2. 2.
    Cannataro, M., Talia, D.: The Knowledge Grid. Communications of the ACM 46, 89–93 (2003)CrossRefGoogle Scholar
  3. 3.
    Fensel, D.: Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce. Springer, Heidelberg (2001)zbMATHGoogle Scholar
  4. 4.
    Fensel, D.: Unifying Reasoning and Search to Web Scale. IEEE Internet Computing 11(2), 94–96 (2007)CrossRefGoogle Scholar
  5. 5.
    Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)Google Scholar
  6. 6.
    Gazzaniga, M.S. (ed.): The Cognitive Neurosciences III. MIT Press, Cambridge (2004)Google Scholar
  7. 7.
    Handy, T.C.: Event-Related Potentials, A Methods Handbook. MIT Press, Cambridge (2004)Google Scholar
  8. 8.
    Hu, J., Zhong, N.: Organizing Multiple Data Sources for Developing Intelligent e-Business Portals. Data Mining and Knowledge Discovery 12(2-3), 127–150 (2006)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Koslow, S.H., Subramaniam, S. (eds.): Databasing the Brain: From Data to Knowledge. Wiley, Chichester (2005)Google Scholar
  10. 10.
    Laird, J.E., van Lent, M.: Human-Level AI’s Killer Application Interactive Computer Games. AI Magazine, 15–25 (Summer 2001)Google Scholar
  11. 11.
    Li, Y., Zhong, N.: Mining Ontology for Automatically Acquiring Web User Information Needs. IEEE Transactions on Knowledge and Data Engineering 18(4), 554–568 (2006)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Liu, J., Zhong, N., Yao, Y.Y., Ras, Z.W.: The Wisdom Web: New Challenges for Web Intelligence (WI). Journal of Intelligent Information Systems 20(1), 5–9 (2003)CrossRefGoogle Scholar
  13. 13.
    Liu, J.: Web Intelligence (WI): What Makes Wisdom Web? In: Proc. Eighteenth International Joint Conference on Artificial Intelligence (IJCAI’03), pp. 1596–1601 (2003)Google Scholar
  14. 14.
    Liu, J., Jin, X., Tsui, K.C.: Autonomy Oriented Computing: From Problem Solving to Complex Systems Modeling. Springer, Heidelberg (2005)zbMATHGoogle Scholar
  15. 15.
    McCarthy, J.: Roads to Human Level AI? Keynote Talk at Beijing University of Technology, Beijing, China (September 2004)Google Scholar
  16. 16.
    Newell, A., Simon, H.A.: Human Problem Solving. Prentice-Hall, Englewood Cliffs (1972)Google Scholar
  17. 17.
    Ohshima, M., Zhong, N., Yao, Y.Y., Liu, C.: Relational Peculiarity Oriented Mining. Data Mining and Knowledge Discovery, Springer (in press)Google Scholar
  18. 18.
    Rosen, B.R., Buckner, R.L., Dale, A.M.: Event-related functional MRI: Past, Present, and Future. Proceedings of National Academy of Sciences, USA 95(3), 773–780 (1998)CrossRefGoogle Scholar
  19. 19.
    Shulman, R.G., Rothman, D.L.: Interpreting Functional Imaging Studies in Terms of Neurotransmitter Cycling. Proceedings of National Academy of Sciences, USA 95(20), 11993–1(1998)CrossRefGoogle Scholar
  20. 20.
    Sternberg, R.J., Lautrey, J., Lubart, T.I.: Models of Intelligence. American Psychological Association (2003)Google Scholar
  21. 21.
    Su, Y., Zheng, L., Zhong, N., Liu, C., Liu, J.: Distributed Reasoning Based on Problem Solver Markup Language (PSML): A Demonstration through Extended OWL. In: Proc. 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE’05), pp. 208–213. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar
  22. 22.
    Su, Y., Liu, J., Zhong, N., Zheng, L., Liu, C.: A Method of Distributed Problem Solving on the Web. In: Proc. 2005 IEEE/WIC/ACM International Conference on Web Intelligence (WI’05), pp. 42–45. IEEE Computer Society Press, Los Alamitos (2005)Google Scholar
  23. 23.
    Turing, A.: Computing Machinery and Intelligence. Mind LIX(236), 433–460 (1950)CrossRefMathSciNetGoogle Scholar
  24. 24.
    Yao, Y.Y., Zhong, N., Liu, J., Ohsuga, S.: Web Intelligence (WI): Research Challenges and Trends in the New Information Age. In: Zhong, N., Yao, Y., Ohsuga, S., Liu, J. (eds.) WI 2001. LNCS (LNAI), vol. 2198, pp. 1–17. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. 25.
    Yao, Y.Y., Zhong, N.: Granular Computing Using Information Tables. In: Lin, T.Y., Yao, Y.Y., Zadeh, L.A. (eds.) Data Mining, Rough Sets and Granular Computing, pp. 102–124. Physica-Verlag, Heidelberg (2002)Google Scholar
  26. 26.
    Zadeh, L.A.: Precisiated Natural Language (PNL). AI Magazine 25(3), 74–91 (2004)Google Scholar
  27. 27.
    Zhong, N., Liu, J., Yao, Y.Y., Ohsuga, S.: Web Intelligence (WI). In: Proc. 24th IEEE Computer Society International Computer Software and Applications Conference (COMPSAC 2000), pp. 469–470. IEEE Computer Society Press, Los Alamitos (2000)CrossRefGoogle Scholar
  28. 28.
    Zhong, N., Liu, C., Ohsuga, S.: Dynamically Organizing KDD Process. International Journal of Pattern Recognition and Artificial Intelligence 15(3), 451–473 (2001)CrossRefGoogle Scholar
  29. 29.
    Zhong, N., Liu, J., Yao, Y.Y.: In Search of the Wisdom Web. IEEE Computer 35(11), 27–31 (2002)Google Scholar
  30. 30.
    Zhong, N.: Representation and Construction of Ontologies for Web Intelligence. International Journal of Foundations of Computer Science 13(4), 555–570 (2002)zbMATHCrossRefGoogle Scholar
  31. 31.
    Zhong, N., Liu, J., Yao, Y.Y. (eds.): Web Intelligence. Springer, Heidelberg (2003)zbMATHGoogle Scholar
  32. 32.
    Zhong, N., Yao, Y.Y., Ohshima, M.: Peculiarity Oriented Multi-Database Mining. IEEE Transaction on Knowlegde and Data Engineering 15(4), 952–960 (2003)CrossRefGoogle Scholar
  33. 33.
    Zhong, N., Wu, J.L., Nakamaru, A., Ohshima, M., Mizuhara, H.: Peculiarity Oriented fMRI Brain Data Analysis for Studying Human Multi-Perception Mechanism. Cognitive Systems Research 5(3), 241–256 (2004)CrossRefGoogle Scholar
  34. 34.
    Zhong, N., Hu, J., Motomura, S., Wu, J.L., Liu, C.: Building a Data Mining Grid for Multiple Human Brain Data Analysis. Computational Intelligence 21(2), 177–196 (2005)CrossRefMathSciNetGoogle Scholar
  35. 35.
    Zhong, N.: Impending Brain Informatics (BI) Research from Web Intelligence (WI) Perspective. International Journal of Information Technology and Decision Making 5(4), 713–727 (2006)CrossRefGoogle Scholar
  36. 36.
    Zhong, N., Liu, J., Yao, Y.Y.: Envisioning Intelligent Information Technologies (iIT) from the Stand-Point of Web Intelligence (WI). Communications of the ACM 50(3), 89–94 (2007)CrossRefGoogle Scholar
  37. 37.
    The OGSA-DAI project: http://www.ogsadai.org.uk/

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Ning Zhong
    • 1
  1. 1.Department of Life Science and Informatics, Maebashi Institute of Technology, Japan &, The International WIC Institute/BJUTChina

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