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A Framework for Intelligent Analysis of Intelligence Data

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Computational Intelligence (IJCCI 2009)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 343))

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Abstract

Intelligent data analysis plays an important role in many application domains. In particular, for detection and prevention of serious crime, including terrorist activity, automated modelling and analysis of intelligence data is of great practical significance. Such an intelligent analysis system will provide useful decision support for intelligence analysts, offering an effective means in the assessment of possible scenarios given observations which may be imprecise and/or uncertain. Intelligent analysis of intelligence data will therefore help to facilitate rapid response in devising and deploying preventive measures. This paper presents an initial approach to the development of a general framework that integrates key component systems for intelligent data analysis, with an application focus on intelligence data. It describes the functionalities of the important component systems and introduces example techniques that are useful to implement such systems. The paper also discusses major challenges and opportunities for further relevant research.

This work was partly supported by UK EPSRC grants GR/S63267/01-02, GR/S98603/01 and EP/D057086/1, and partly by a UK Royal Academy of Engineering/Daphne Jackson Research Fellowship. The authors are grateful to all members of the project teams for their contributions, but will take full responsibility for the views expressed here.

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References

  1. Aitken, C., Shen, Q., Jensen, R., Hayes, B.: The evaluation of evidence for exponentially distributed data. Computational Statistics and Data Analysis 51, 5682–5693 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  2. Baranyi, P., Koczy, L., Gedeon, T.: A generalized concept for in fuzzy rule interpolation. IEEE Transactions on Fuzzy Systems 12(6), 820–837 (2004)

    Article  Google Scholar 

  3. Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American, 34–43 (May 2001)

    Google Scholar 

  4. CNN: A Day of Terror (September 11, 2001), http://www.cnn.com/2003/US/03/10/sprj.80.2001.terror/index.html

  5. Berthold, M., Hand, D.: Intelligent Data Analysis: An Introduction, 2nd edn. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  6. Boongoen, T., Shen, Q.: Nearest-neighbor guided evaluation of data reliability and its applications. IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics (to appear)

    Google Scholar 

  7. Boongoen, T., Shen, Q., Price, P.: Disclosing false identity through hybrid link analysis. Artificial Intelligence and Law 18(1), 77–102 (2010)

    Article  Google Scholar 

  8. Buyukozkan, G., Ruan, D.: Choquet integral based aggregation approach to software development risk assessment. Information Sciences 180, 441–451 (2010)

    Article  Google Scholar 

  9. Calado, P., Cristo, M., Goncalves, M., de Moura, E., Ribeiro-Neto, E., Ziviani, N.: Link based similarity measures for the classification of web documents. Journal of American Society fo Information Science and Technology 57(2), 208–221 (2006)

    Article  Google Scholar 

  10. Chen, S., Huang, Y.: Relative risk aversion and wealth dynamics. Information Sciences 177, 1222–1229 (2007)

    Article  MathSciNet  Google Scholar 

  11. Chouchoulas, A., Shen, Q.: Rough set-aided keyword reduction for text categorisation. Applied Artificial Intelligence 15(9), 843–873 (2001)

    Article  Google Scholar 

  12. Darby J.: Estimating terrorist risk with possibility theory (2004), http://www.doe.gov/bridge

  13. de Kleer, J.: An assumption-based TMS. Artificial Intelligence 28(2), 127–162 (1986)

    Article  Google Scholar 

  14. Dubois, D., Prade, H.: Rough fuzzy sets and fuzzy rough sets. International Journal of General Systems 17, 191–209 (1990)

    Article  MATH  Google Scholar 

  15. Fu, X., Boongoen, T., Shen, Q.: Evidence directed generation of plausible crime scenarios with identity resolution. Applied Artificial Intelligence 24(4), 253–276 (2010)

    Article  Google Scholar 

  16. Fu, X., Shen, Q.: Fuzzy compositional modeling. IEEE Transactions on Fuzzy Systems 18(4), 823–840 (2010)

    Article  Google Scholar 

  17. Halliwell, J., Shen, Q.: Linguistic probabilities: theory and application. Soft Computing 13(2), 169–183 (2009)

    Article  MATH  Google Scholar 

  18. Huang, C., Inoue, H.: Soft risk maps of natural disasters and their applications to decision-making. Information Sciences 177, 1583–1592 (2007)

    Article  MATH  Google Scholar 

  19. Huang, Z., Shen, Q.: Fuzzy interpolative and extrapolative reasoning: a practical approach. IEEE Transactions on Fuzzy Systems 16(1), 13–28 (2008)

    Article  Google Scholar 

  20. Huang, Z., Shen, Q.: Fuzzy interpolative reasoning via scale and move transformation. IEEE Transactions on Fuzzy Systems 14(2), 340–359 (2006)

    Article  Google Scholar 

  21. Jensen, R., Shen, Q.: Are more features better? IEEE Transactions on Fuzzy Systems 17(6), 1456–1458 (2009)

    Article  Google Scholar 

  22. Jensen, R., Shen, Q.: New approaches to fuzzy-rough feature selection. IEEE Transactions on Fuzzy Systems 17(4), 824–838 (2009)

    Article  Google Scholar 

  23. Jensen, R., Shen, Q.: Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches. IEEE and Wiley (2008)

    Google Scholar 

  24. Jensen, R., Shen, Q.: Fuzzy-rough sets assisted attribute selection. IEEE Transactions on Fuzzy Systems 15(1), 73–89 (2007)

    Article  Google Scholar 

  25. Jensen, R., Shen, Q.: Semantics-preserving dimensionality reduction: Rough and fuzzy-rough approaches. IEEE Transactions on Knowledge and Data Engineering 16(12), 1457–1471 (2004)

    Article  Google Scholar 

  26. Keppens, J., Shen, Q.: On compositional modelling. Knowledge Engineering Review 16(2), 157–200 (2001)

    Article  MATH  Google Scholar 

  27. Keppens, J., Shen, Q., Price, C.: Compositional Bayesian modelling for computation of evidence collection strategies. Applied Intelligence (to appear)

    Google Scholar 

  28. King, R., Rowland, J., Oliver, S., Young, M., Aubrey, W., Byrne, E., Liakata, M., Markham, M., Pir, P., Soldatova, L., Sparkes, A., Whelan, K.E., Clare, A.: The automation of science. Science 324(5923), 85–89 (2009)

    Article  Google Scholar 

  29. Koyuncu, M., Yazici, A.: A fuzzy knowledge-based system for intelligent retrieval. IEEE Transactions on Fuzzy Systems 13(3), 317–330 (2005)

    Article  Google Scholar 

  30. Kwakernaak, H.: Fuzzy random variables – I. Information Sciences 15, 1–29 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  31. Kwakernaak, H.: Fuzzy random variables – II. Information Sciences 17, 253–278 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  32. Liben-Nowell, D., Kleinberg, J.: The link-prediction problem for social networks. Journal of American Society for Information Science and Technology 58(7), 1019–1031 (2007)

    Article  Google Scholar 

  33. Kriete, A., Eils, R.: Computational Systems Biology. Elsevier, Amsterdam (2005)

    Google Scholar 

  34. Liu, H., Motoda, H.: Feature Selection for Knowledge Discovery and Data Mining. Springer, Heidelberg (1998)

    Book  MATH  Google Scholar 

  35. Mac Parthalain, N., Shen, Q.: Exploring the boundary region of tolerance rough sets for feature selection. Pattern Recognition 42(5), 655–667 (2009)

    Article  MATH  Google Scholar 

  36. Mac Parthalain, N., Shen, Q., Jensen, R.: A distance measure approach to exploring the rough set boundary region for attribute reduction. IEEE Transactions on Knowledge and Data Engineering (to appear)

    Google Scholar 

  37. Marín-Blázquez, J., Shen, Q.: From approximative to descriptive fuzzy classifiers. IEEE Transactions on Fuzzy Systems 10(4), 484–497 (2002)

    Article  Google Scholar 

  38. Miguel, I., Shen, Q.: Fuzzy rrDFCSP and planning. Artificial Intelligence 148(1-2), 11–52 (2003)

    Article  MathSciNet  Google Scholar 

  39. Mohtadi, H.: Assessing the risk of terrorism using extreme value statistics. In: Proceedings of the Institute of Food Technologists First Annual Conference on Food Protection and Defencse (2005)

    Google Scholar 

  40. Puri, M., Ralescu, D.: Fuzzy random variables. Journal of Mathematical Analysis and Applications 114, 409–422 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  41. Parsons, S.: Qualitative probability and order of magnitude reasoning. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11(3), 373–390 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  42. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers, Dordrecht (1991)

    Book  MATH  Google Scholar 

  43. Perner, P.: Intelligent data analysis in medicine: Recent advances. Artificial Intelligence in Medicine 37(1), 1–5 (2006)

    Article  Google Scholar 

  44. Raiman, O.: Order-of-magnitude reasoning. Artificial Intelligence 51, 11–38 (1991)

    Article  Google Scholar 

  45. Shadbolt, N., Hall, W., Berners-Lee, T.: The semantic web revisited. IEEE Intelligent Systems 21(3), 96–101 (2006)

    Article  Google Scholar 

  46. Shen, Q.: Intelligent systems for decision support. In: Proceedings of International Joint Conference on Computational Intelligence, pp. 25–36 (2009)

    Google Scholar 

  47. Shen, Q., Chouchoulas, A.: A rough-fuzzy approach for generating classification rules. Pattern Recognition 35(11), 2425–2438 (2002)

    Article  MATH  Google Scholar 

  48. Shen, Q., Jensen, R.: Selecting informative features with fuzzy-rough sets and its application for complex systems monitoring. Pattern Recognition 37(7), 1351–1363 (2004)

    Article  MATH  Google Scholar 

  49. Shen, Q., Keppens, J., Aitken, C., Schafer, B., Lee, M.: A scenario driven decision support system for serious crime investigation. Law, Probability and Risk 5(2), 87–117 (2006)

    Article  Google Scholar 

  50. Shen, Q., Zhao, R.: Risk assessment of serious crime with fuzzy random theory. Information Sciences (to appear)

    Google Scholar 

  51. Shen, Q., Zhao, R.: A credibilistic approach to assumption-based truth maintenance. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans (to appear)

    Google Scholar 

  52. Shen, Q., Zhao, R., Tang, W.: Modelling random fuzzy renewal reward processes. IEEE Transactions on Fuzzy Systems 16(5), 1379–1385 (2008)

    Article  Google Scholar 

  53. Tikk, D., Baranyi, P.: Comprehensive analysis of a new fuzzy rule interpolation method. IEEE Transactions on Fuzzy Systems 8(3), 281–296 (2000)

    Article  Google Scholar 

  54. Tsang, E., Chen, D., Yeung, D., Wang, X., Lee, J.: Attributes reduction using fuzzy rough sets. IEEE Transactions on Fuzzy Systems 16(5), 1130–1141 (2008)

    Article  Google Scholar 

  55. Wesbury B.: The Economic Cost of Terrorism, http://usinfo.state.gov/topical/econ/mlc/02091004.htm

  56. Willis H., Morral A., Kelly T., Medby J.: Estimating terrorism risk, RAND Corporation, Report from Center for Terrorism Risk Management Policy (2005), http://www.rand.org

  57. Woo, G.: Terrorism risk. In: Voeller, J. (ed.) Handbook of Science and Technology for Homeland Security. Wiley, Chichester (2007)

    Google Scholar 

  58. Yang, L., Shen, Q.: Adaptive fuzzy interpolation. IEEE Transactions on Fuzzy Systems (to appear)

    Google Scholar 

  59. Zadeh, L.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 100, 9–34 (1999)

    Article  Google Scholar 

  60. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning I. Information Sciences 8, 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  61. Zadeh, L.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

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Authors and Affiliations

  1. Dept. of Computer Science, Aberystwyth University, Wales, U.K.

    Qiang Shen & Changjing Shang

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  1. Qiang Shen
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  2. Changjing Shang
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Correspondence to Qiang Shen .

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Editors and Affiliations

  1. Images, Signals and Intelligence Systems Laboratory, University PARIS-EST Creteil (UPEC), LISSI EA 3956, Paris 12, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica Polo II - Pinhal de Marrocos, University of Coimbra, 3030, Coimbra, Portugal

    António Dourado Correia

  3. Evolutionary Systems and Biomedical Engineering Lab, Instituto Superior Tecnico IST Systems and Robotics Institute, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Agostinho Rosa

  4. Polytechnic Institute of Setúbal / INSTICC, 2910-595, Setubal, Portugal

    Joaquim Filipe

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Shen, Q., Shang, C. (2011). A Framework for Intelligent Analysis of Intelligence Data. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2009. Studies in Computational Intelligence, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20206-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-20206-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20205-6

  • Online ISBN: 978-3-642-20206-3

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