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Building a Brain-Informatics Portal on the Wisdom Web with a Multi-layer Grid: A New Challenge for Web Intelligence Research

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Modeling Decisions for Artificial Intelligence (MDAI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3558))

Abstract

Web Intelligence (WI) presents excellent opportunities and challenges for the research and development of new generation of Web-based information processing technology, as well as for exploiting Web-based advanced applications. In this paper, we give a new perspective of WI research: Web Intelligence meets Brain Informatics. We observe that new instrumentation (fMRI etc.) and advanced IT are causing an impending revolution in WI and Brain Sciences (BS). We propose a way to build a Brain-Informatics portal by using WI technologies, which is of great benefit to both WI and BS researches.

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References

  1. Banquet, J.P.: Spectral Analysis of the EEG in Meditation. Electroencephalography and Clinical Neurophysiology 35, 143–151 (1973)

    Article  Google Scholar 

  2. Banfield, J., Raftery, A.: Model-based Gaussian and Non-Gaussian Clustering. Biometrics 49, 803–821 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  3. Cannataro, M., Talia, D.: The Knowledge Grid. CACM 46, 89–93 (2003)

    Google Scholar 

  4. Berman, F.: From TeraGrid to Knowledge Grid. CACM 44, 27–28 (2001)

    Google Scholar 

  5. Cerutti, S., Chiarenza, G., Liberati, D., Mascellani, P., Pavesi, G.: A Parametric Method of Identification of Single Trial Event-related Potentials in the Brain. IEEE Trans. Biomed. Eng. 35(9), 701–711 (1988)

    Article  Google Scholar 

  6. Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)

    Google Scholar 

  7. Hornero, R., Martin-Fernandez, M., Alonso, A., Izquierdo, A., Lopez, M.: A DSP Implementation of Wavelet Transform to Detect Epileptiform Activity in the EEG. In: Proc. 8th Annual International Conference on Signal Processing Applications and Technology ICAPAT 1997, pp. 692–696 (1997)

    Google Scholar 

  8. Hu, J., Zhong, N.: Organizing Dynamic Multi-level Workflows on Multi-layer Grids for e-Business Portals Development. In: Proc. 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE 2005), pp. 196–201. IEEE Press, Los Alamitos (2005)

    Google Scholar 

  9. Liu, C., Zhong, N., Ohsuga, S.: A Multi-agent Based Architecture for Distributed KDD Process. In: Ohsuga, S., Raś, Z.W. (eds.) ISMIS 2000. LNCS (LNAI), vol. 1932, pp. 591–600. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  10. 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)

    Article  Google Scholar 

  11. Liu, J.: Web Intelligence (WI): What Makes Wisdom Web? In: Proc. Eighteenth International Joint Conference on Artificial Intelligence (IJCAI 2003), pp. 1596–1601 (2003)

    Google Scholar 

  12. Liu, J., Jin, X., Tang, Y.: Multi-agent Collaborative Service and Distributed Problem Solving. Cognitive Systems Research 5(3), 191–206 (2004)

    Article  Google Scholar 

  13. McCarthy, J.: Roads to Human Level AI?, September 2004. Beijing University of Technology, Beijing Keynote Talk at (2004)

    Google Scholar 

  14. Megalooikonomou, V., Davatzikos, C., Herskovits, E.H.: Mining Lesion-Deficit Associations in a Brain Image Database. In: Proc. Fifth International Conference on Knowledge Discovery and Data Mining (KDD 1999), pp. 347–351. ACM Press, New York (1999)

    Chapter  Google Scholar 

  15. Megalooikonomou, V., Ford, J., Shen, L., Makedon, F., Saykin, A.: Data Mining in Brain Imaging. Statistical Methods in Medical Research 9, 359–394 (2000)

    Article  MATH  Google Scholar 

  16. Megalooikonomou, V., Herskovits, E.H.: Mining Structure-Function Associations in a Brain Image Database. In: Cios, K.J. (ed.) Medical Data Mining and Knowledge Discovery, pp. 153–179. Physica, New York (2001)

    Google Scholar 

  17. Mitchell, T.M., Hutchinson, R., Just, M., Niculescu, R.S., Pereira, F., Wang, X.: Classifying Instantaneous Cognitive States from fMRI Data. In: Proc. American Medical Informatics Association Annual Symposium, pp. 465–469 (2003)

    Google Scholar 

  18. Motomura, S., Zhong, N., Wu, J.L.: Brain Waves Data Mining for Human Multi-perception Activity Analysis. In: Proc. Inter. Workshop on Advanced Technologies for e-Learning and e-Science (ATELS 2004), pp. 65–72 (2004)

    Google Scholar 

  19. Sternberg, R.J., Lautrey, J., Lubart, T.I.: Models of Intelligence. American Psychological Association, Hyattsville (2003)

    Google Scholar 

  20. 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 2005), pp. 208–213. IEEE Press, Los Alamitos (2005)

    Google Scholar 

  21. Tomita, K., Zhong, N., Yamauchi, H.: Coupling Global Semantic Web with Local Information Sources for Problem Solving. In: Proc. First International Workshop on Semantic Web Mining and Reasoning (SWMR 2004), pp. 66–74 (2004)

    Google Scholar 

  22. Tsukimoto, H., Morita, C.: The Discovery of Rules from Brain Images. In: Arikawa, S., Motoda, H. (eds.) DS 1998. LNCS (LNAI), vol. 1532, Springer, Heidelberg (1998)

    Google Scholar 

  23. 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)

    Chapter  Google Scholar 

  24. Zadeh, L.A.: Precisiated Natural Language (PNL). AI Magazine 25(3), 74–91 (2004)

    Google Scholar 

  25. 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 CS Press, Los Alamitos (2000)

    Google Scholar 

  26. Zhong, N., Liu, C., Ohsuga, S.: Dynamically Organizing KDD Process. International Journal of Pattern Recognition and Artificial Intelligence 15(3), 451–473 (2001)

    Article  Google Scholar 

  27. Zhong, N.: Representation and Construction of Ontologies for Web Intelligence. International Journal of Foundations of Computer Science 13(4), 555–570 (2002)

    Article  MATH  Google Scholar 

  28. Zhong, N., Liu, J., Yao, Y.Y.: In Search of the Wisdom Web. IEEE Computer 35(11), 27–31 (2002)

    Google Scholar 

  29. Zhong, N., Liu, J., Yao, Y.Y. (eds.): Web Intelligence. Springer, Heidelberg (2003)

    MATH  Google Scholar 

  30. Zhong, N., Yao, Y.Y., Ohshima, M.: Peculiarity Oriented Multi-Database Mining. IEEE Transaction on Knowlegde and Data Engineering 15(4), 952–960 (2003)

    Article  Google Scholar 

  31. Zhong, N.: Developing Intelligent Portals by Using WI Technologies. In: Li, J.P., et al. (eds.) Wavelet Analysis and Its Applications, and Active Media Technology, vol. 2, pp. 555–567. World Scientific, Singapore (2004)

    Google Scholar 

  32. 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)

    Article  Google Scholar 

  33. Zhong, N., Liu, J. (eds.): Intelligent Technologies for Information Analysis. Springer, Heidelberg (2004)

    MATH  Google Scholar 

  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)

    Article  MathSciNet  Google Scholar 

  35. Zhong, N., Motomura, S., Wu, J.L.: Peculiarity Oriented Multi-Aspect Brain Data Analysis for Studying Human Multi-Perception Mechanism. In: Proc. SAINT 2005 Workshops (Workshop 8: Computer Intelligence for Exabyte Scale Data Explosion), pp. 306–309. IEEE Computer Society Press, Los Alamitos (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. The International WIC Institute &, Department of Information Engineering, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, Maebashi-City, 371-0816, Japan

    Ning Zhong

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  1. Ning Zhong
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Editor information

Editors and Affiliations

  1. IIIA, Artificial Intelligence Research Institute CSIC, Spanish National Research Council, Campus UAB s/n, 08193, Bellaterra, Catalonia, Spain

    Vicenç Torra

  2. Toho Gakuen, 3-1-10 Naka, Kunitachi, 186-0004, Tokyo, Japan

    Yasuo Narukawa

  3. Department of Risk Engineering, School of Systems and Information Engineering, University of Tsukuba, 305-8573, Ibaraki, Japan

    Sadaaki Miyamoto

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© 2005 Springer-Verlag Berlin Heidelberg

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Zhong, N. (2005). Building a Brain-Informatics Portal on the Wisdom Web with a Multi-layer Grid: A New Challenge for Web Intelligence Research. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2005. Lecture Notes in Computer Science(), vol 3558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526018_4

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  • DOI: https://doi.org/10.1007/11526018_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27871-9

  • Online ISBN: 978-3-540-31883-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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