Skip to main content
SpringerLink
Log in

Computational Theory Perception (CTP), Rough-Fuzzy Uncertainty Analysis and Mining in Bioinformatics and Web Intelligence: A Unified Framework

  • Chapter
Transactions on Rough Sets XI

Part of the book series: Lecture Notes in Computer Science ((TRS,volume 5946))

Abstract

The concept of computational theory of perceptions (CTP), its characteristics and the relation with fuzzy-granulation (f-granulation) are explained. Role of f-granulation in machine and human intelligence and its modeling through rough-fuzzy integration are discussed. The Significance of rough-fuzzy synergestic integration is highlighted through three examples, namely, rough-fuzzy case generation, rough-fuzzy c-means and rough-fuzzy c-medoids along with the role of fuzzy granular computation. Their superiority, in terms of performance and computation time, is illustrated for the tasks of case generation (mining) in large-scale case-based reasoning systems, segmenting brain MR images, and analyzing protein sequences. Different quantitative measures for rough-fuzzy clustering are explained. The effectiveness of rough sets in constructing an ensemble classifier is also illustrated in a part of the article along with its performance for web service classification. The article includes some of the existing results published elsewhere under different topics related to rough sets and attempts to integrate them with CTP in a unified framework providing a new direction of research.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baldi, P., Brunak, S.: Bioinformatics: The Machine Learning Approach. MIT Press, Cambridge (1998)

    Google Scholar 

  2. Banerjee, M., Mitra, S., Pal, S.K.: Rough Fuzzy MLP: Knowledge Encoding and Classification. IEEE Trans. Neural Networks 9, 1203–1216 (1998)

    Article  Google Scholar 

  3. Bezdek, J.C.: Pattern Recognition with Fuzzy Objective Function Algorithm. Plenum, New York (1981)

    Google Scholar 

  4. Dayhoff, M.O., Schwartz, R.M., Orcutt, B.C.: A Model of Evolutionary Change in Proteins. Matrices for Detecting Distant Relationships, Atlas of Protein Sequence and Structure 5, 345–358 (1978)

    Google Scholar 

  5. Han, J., Kamber, M.: Data Mining: Concepts and Techniques. Morgan Kaufmann, San Francisco (2005)

    Google Scholar 

  6. http://www.daviddlewis.com/resources/testcollections/reuters21578/

  7. http://www.cs.cmu.edu/~WebKB/

  8. http://www.dmoz.org/

  9. http://www.looksmart.com

  10. Kolodner, J.L.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)

    Google Scholar 

  11. Krishnapuram, R., Joshi, A., Nasraoui, O., Yi, L.: Low complexity fuzzy relational clustering algorithms for web mining. IEEE Trans. on Fuzzy System 9, 595–607 (2001)

    Article  Google Scholar 

  12. Kuipers, B.J.: Qualitative Reasoning. MIT Press, Cambridge (1984)

    Google Scholar 

  13. Li, Y., Shiu, S.C.K., Pal, S.K.: Combining feature reduction and case selection in building CBR classifiers. IEEE Trans. on Knowledge and Data Engineering 18, 415–429 (2006)

    Article  Google Scholar 

  14. Lingras, P., West, C.: Interval set clustering of web users with rough K-means. Journal of Intelligent Information Systems 23, 5–16 (2004)

    Article  MATH  Google Scholar 

  15. Maji, P., Pal, S.K.: Rough set based generalized fuzzy C-means algorithm and quantitative indices. IEEE Trans. on System, Man and Cybernetics, Part B, 37, 1529–1540 (2007)

    Article  Google Scholar 

  16. Maji, P., Pal, S.K.: Rough-fuzzy C-medoids algorithm and selection of bio-basis for amino acid sequence analysis. IEEE Trans. Knowledge and Data Engineering 19, 859–872 (2007)

    Article  Google Scholar 

  17. Maji, P., Pal, S.K.: Feature Selection Using f-Information Measures in Fuzzy Approximation Spaces. IEEE Trans. Knowledge and Data Engineering (to appear)

    Google Scholar 

  18. Mitra, S., Banka, H., Pedrycz, W.: Rough-fuzzy collaborative clustering. IEEE Trans. on Systems, Man, and Cybernetics - Part B: Cybernetics 36, 795–805 (2006)

    Article  Google Scholar 

  19. Mitra, S., De, R.K., Pal, S.K.: Knowledge Based Fuzzy MLP for Classification and Rule Generation. IEEE Trans. Neural Networks 8, 1338–1350 (1997)

    Article  Google Scholar 

  20. National Center for Biotechnology Information, http://www.ncbi.nlm.nih.gov

  21. Pal, S.K., Talwar, V., Mitra, P.: Web mining in soft computing framework: Relevance, state of the art and future directions. IEEE Trans. Neural Networks 13, 1163–1177 (2002)

    Article  Google Scholar 

  22. Pal, S.K., Bandyopadhyay, S., Ray, S.S.: Evolutionary Computation in Bioinformatics: A Review. IEEE Transactions on Systems, Man, and Cybernetics, Part-C 36, 601–615 (2006)

    Article  Google Scholar 

  23. Pal, S.K., Skowron, A. (eds.): Rough-Fuzzy Hybridization: A New Trend in Decision Making. Springer, Singapore (1999)

    MATH  Google Scholar 

  24. Pal, S.K., Polkowski, L., Skowron, A. (eds.): Rough-neuro Computing: A Way to Computing with Words. Springer, Berlin (2003)

    Google Scholar 

  25. Pal, S.K., Skowron, A. (eds.): Special issue on Rough Sets, Pattern Recognition and Data Mining. Pattern Recognition Letters 24 (2003)

    Google Scholar 

  26. Pal, S.K., Dillon, T.S., Yeung, D.S. (eds.): Soft Computing in Case Based Reasoning. Springer, London (2001)

    MATH  Google Scholar 

  27. Pal, S.K., Shiu, S.C.K.: Foundations of Soft Case Based Reasoning. John Wiley, NY (2003)

    Google Scholar 

  28. Pal, S.K., Mitra, P.: Case generation using rough sets with fuzzy discretization. IEEE Trans. Knowledge and Data Engineering 16, 292–300 (2004)

    Article  Google Scholar 

  29. Pal, S.K., Mitra, P.: Pattern Recognition Algorithms for Data Mining. Chapman & Hall CRC Press, Boca Raton (2004)

    MATH  Google Scholar 

  30. Pal, S.K., Ghosh, A., Sankar, B.U.: Segmentation of remotely sensed images with fuzzy thresholding, and quantitative evaluation. International Journal of Remote Sensing 2, 2269–2300 (2000)

    Google Scholar 

  31. Pal, S.K., Polkowski, L., Skowron, A. (eds.): Rough-Neural Computing Techniques for Computing with Words. Springer, Berlin (2004)

    MATH  Google Scholar 

  32. Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds.): PReMI 2005. LNCS, vol. 3776. Springer, Heidelberg (2005)

    Google Scholar 

  33. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic, Dordrecht (1991)

    MATH  Google Scholar 

  34. Pedrycz, W., Skowron, A., Kreinovich, V. (eds.): Handbook of Granular Computing. John Wiley, N.Y. (2008)

    Google Scholar 

  35. Ray, S.S., Bandyopadhyay, S., Mitra, P., Pal, S.K.: Bioinformatics in Neurocomputing Framework. IEE Proc. Circuits Devices & Systems 152, 556–564 (2005)

    Article  Google Scholar 

  36. Saha, S., Murthy, C.A., Pal, S.K.: Rough set Based Ensemble Classifier for Web Page Classification. Fundamentae Informetica 76, 171–187 (2007)

    MathSciNet  Google Scholar 

  37. Saha, S., Murthy, C.A., Pal, S.K.: Classification of Web Services using Tensor Space Model and Rough Ensemble Classifier. In: Proc. 17th International Symposium on Methodologies for Intelligent Systems, Toronto, Canada, pp. 508–513 (2008)

    Google Scholar 

  38. Sen, D., Pal, S.K.: Histogram Thresholding using Fuzzy and Rough Measures of Association Error. IEEE Trans. Image Processing 18, 879–888 (2009)

    Article  Google Scholar 

  39. Sen, D., Pal, S.K.: Generalized Rough Sets, Entropy and Image Ambiguity Measures. IEEE Trans. Syst, Man and Cyberns. Part B 39, 117–128 (2009)

    Article  Google Scholar 

  40. Sun, R.: Integrating Rules and Connectionism for Robust Commonsense Reasoning. Wiley, N.Y. (1994)

    MATH  Google Scholar 

  41. Swiniarski, R.W., Skowron, A.: Rough Set Methods in Feature Selection and Recognition. Pattern Recognition Letters 24, 833–849 (2003)

    Article  MATH  Google Scholar 

  42. Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.): RSKT 2008. LNCS (LNAI), vol. 5009. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  43. Yao, Y.Y.: Granular Computing: Basic Issues and Possible Solutions. In: Proceedings of the 5th Joint Conference on Information Sciences, vol. I, pp. 186–189 (2000)

    Google Scholar 

  44. Zadeh, L.A.: A new direction in AI: Toward a computational theory of perceptions. AI Magazine 22, 73–84 (2001)

    Google Scholar 

  45. Zadeh, L.A., Pal, S.K., Mitra, S.: Foreword. In: Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing. Wiley, New York (1999)

    Google Scholar 

  46. Zadeh, L.A.: Fuzzy Logic, Neural Networks, and Soft Computing. ACM 37, 77–84 (1994)

    Article  Google Scholar 

  47. Zadeh, L.A.: Towards a Theory of Fuzzy Information Granulation and Its Centrality in Human Reasoning and Fuzzy Logic. Fuzzy Sets Systems 19, 111–127 (1997)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Soft Computing Research: A National Facility, Indian Statistical Institute, Kolkata, 700108

    Sankar K. Pal

Authors
  1. Sankar K. Pal
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. University of Manitoba, Department of Electrical and Computer Engineering, , , ,, Winnipeg, R3T 5V6, Manitoba, Canada

    James F. Peters

  2. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Pal, S.K. (2010). Computational Theory Perception (CTP), Rough-Fuzzy Uncertainty Analysis and Mining in Bioinformatics and Web Intelligence: A Unified Framework. In: Peters, J.F., Skowron, A. (eds) Transactions on Rough Sets XI. Lecture Notes in Computer Science, vol 5946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11479-3_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-11479-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-11478-6

  • Online ISBN: 978-3-642-11479-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation