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Rough Sets and Current Trends in Computing. Proceedings. 3rd International Conference, Malvern, PA, October 14 16, 2002. Lecture Notes in Computer Science 2475. Berlin: Springer. 2002. 6. K. K. Ang and C. Quek. Stock trading using RSPOP: a novel rough set-based neuro-fuzzy approach. IEEE Trans. Neural Net. 17(5): 1301 1315. 2006. 7. C. Apt , F. Damerau, and S. M. Weiss. Automated learning of decision rules for e text categorization. ACM Trans. Inf. Sys. 12(3): 233 251. 1994. 8. S. Asharaf and M. N. Murty. An adaptive rough fuzzy single pass algorithm for clustering large data sets. Pattern Recog. 36(12): 3015 3018. 2004. 9. S. Asharaf, S. K. Shevade, and N. M. Murty. Rough support vector clustering. Pattern Recog. 38(10): 1779 1783. 2005. 10. J. Atkinson-Abutridy, C. Mellish, and S. Aitken. Combining information extraction with genetic algorithms for text mining. IEEE Intelligent Systems 19(3): 22 30. 2004. 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Pradhan. A cluster-based approach for routing in dynamic networks. ACM SIGCOMM Computer Communication Review, 27(2):49 65, 1997. 14. M. Gerla and J. T.-C. Tsai. Multicluster, mobile, multimedia radio network. ACM/Kluwer Journal of Wireless Networks, 1(3):255 265, 1995. 15. R. Ramanathan and M. Steenstrup. Hierarchically-organized, multihop mobile wireless networks for quality-of-service support. ACM/Baltzer Mobile Networks and Applications, 3(1):101 119, 1998. 16. R. Krishnan, R. Ramanathan, and M. Steenstrup. Optimization algorithms for large selfStructuring networks. In Proceedings of the Conference on Computer Communications, Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 1999), Vol. 1, March 1999, pp. 71 78. 17. H. Zhang and A. Arora. GS 3 : Scalable self-con guration and self-healing in wireless networks. 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