System and method for organizing, compressing and...

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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C707S793000, C707S793000, C707S793000

Reexamination Certificate

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06941303

ABSTRACT:
A system and method to take data, which is in the form of an n-dimensional array of binary data where the binary data is comprised of bits that are identified by a bit position within the n-dimensional array, and create one file for each bit position of the binary data while maintaining the bit position identification and to store the bit with the corresponding bit position identification from the binary data within the created filed. Once this bit-sequential format of the data is achieved, the formatted data is structured into a tree format that is data-mining-ready. The formatted data is structured by dividing each of the files containing the binary data into quadrants according to the bit position identification and recording the count of 1-bits for each quadrant on a first level. Then, recursively dividing each of the quadrants into further quadrants and recording the count of 1-bits for each quadrant until all quadrants comprise a pure-1 quadrant or a pure-0 quadrant to form a basic tree structure.

REFERENCES:
patent: 5715455 (1998-02-01), Macon et al.
patent: 5960437 (1999-09-01), Krawchuk et al.
patent: 5987468 (1999-11-01), Singh et al.
patent: 6185561 (2001-02-01), Balaban et al.
Adalhkula, Srivani, “Augmenting Data Structures”, Sep. 9, 1998, Lecture notes for Data Structures and Algorithms <http://www.msci.memphis.edu/˜giri/7713/f98/lec3.html>.
Bayardo, Roberto J., “Brute-Force Mining of High-Confidence Classification Rules”, 1997, Proc. of the Third Int'l Conf. on Knowledge Discovery & Data Mining pp. 123-126.
Oualline, Steve, “Practical C++ Programming”, 1997, O'Reilly & Associates, pp. 167-176.
“Mining Association Rules Between Sets of Items in Large Database,” R. Agrawal, T. Imielinski, A. Swami, ACM-SIGMOD 93, Washington, D.C., pp. 207-216, May 1993.
“Fast Algorithms for Mining Association Rules,” R. Agrawal, R. Srikant, Proceedings of the International Conference on VLDB, Santiago, Chile, 13 pgs., Sep. 1994.
“Mining Quantitative Association Rules in Large Relational Tables,” R. Srikant, R. Agrawal, ACM-SIGMOD 96, Montreal, Canada, pp. 1-12, Jun. 1996.
“An Effective Hash-Based Algorithm for Mining Association Rules,” J.S. Park, M.S. Chen, P.S. Yu, ACM-SIGMOD 95, California, pp. 175-186, 1995.
“Multidimensional Access Methods,” V. Gaede, O. Gunther, ACM Computing Surveys, vol. 30, No. 2, pp. 171-231, Jun. 1998.
“The Quadtree and Related Hierarchical Data Structure,” H. Samet, ACM Computing Survey, vol. 16, No. 2, pp. 188-260, Jun. 1984.
“Quad Trees: A Data Structure for Retrieval of Composite Keys,” R.A. Finkel, J.L. Bentley, Acta Informatica, vol. 4, pp. 1-9, 1974.
Web site print-out: “What are HH-codes and how can they be used to store hydrographic data?,” H. Iverson, Norwegian Hyrdorgraphic Service (NHS), http://www.statkart.no
lhdb/iveher/hhtext.htm, 7 pgs., Jan. 1998.
“Run-Length Encodings,” S.W. Golomb, IEEE Trans. On Information Theory, vol. 12, No. 3, pp. 399-401, Jul. 1966.
“Mining Frequent Patterns Without Candidate Generation,” J. Han, J. Pei, Y. Yin, ACM-SIGMOD 2000, Dallas, Texas, pp. 1-12, May 2000.
“Spatial Data Mining: A Database Approach,” M. Ester, H-P. Kriegel, J. Sander, Proceedings of the Fifth International Symposium on Large Spatial Databases (SSD), Berlin, Germany, 20 pgs., 1997.
“Spatial Data Mining: Progress and Challenges Survey Paper,” K. Koperski, J. Adhikary, J. Han, Data Mining and Knowledge Discovery, 16 pgs., 1996.
“Spatial Data Mining: Database Primitives, Algorithms and Efficient DBMS Support,” M. Ester, A. Frommelt, H-P. Kriegel, J. Sander, Data Mining and Knowledge Discovery, 28 pgs., 1999.
“Discovery of Spatial Association Rules in Geographic Information Databases,” K. Koperski, J. Han, SSD, 20 pgs., 1995.
Web site print-out:SMILEY(Spatial Miner&Interface Language for Earth Yield), Database Systems Users & Research Group at NDSU (DataSURG) http://www.midas.cs.ndsu.nodak.edu/˜smiley, 5 pgs., undated.
“The Application of Association Rule Mining on Remotely Sensed Data.” J. Dong, W. Perrizo, Q. Ding, J. Zhou, Proceedings of ACM Symposium on Applied Computers, Italy, 6 pgs., Mar. 2000.
“Brute-Force Mining of High-Confidence Classification Rules,” R.J. Bayardo, Jr., Knowledge Discovery & Data Mining, pp. 123-126, 1997.
“Finding Interesting Associations Without Support Pruning,” E. Cohen, M. Datar, S. Fujiwara, A. Gionis, P. Indyk, R. Motwani, J. Ullman, C. Yang, Proceedings of 26th International Conference on Very Large Data Bases, Cairo, Egypt, 12 pgs., Sep. 2000.
“Growing Decision Trees on Support-Less Association Rules,” K. Wang S. Zhou, Y. He, 6thACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Boston, Massachusetts, 5 pgs., Aug. 2000.
“Integrating Classification and Association Rule Mining,” B. Liu, W. Hsu, Y. Ma, The Fourth International Conference on Knowledge Discovery and Data Mining, New York, New York, 7 pgs., Aug. 1998.
“Inferring Decision Trees Using the Minimum Description Length Principle,” J.R. Quinlan, R.L. Rivest, Information and Computation, Academic Press, Inc., vol. 80, pp. 227-248, 1989.
“An Interval Classifier for Database Mining Applications,” R. Agrawal, S. Ghosh, T. Imielinski, B. Iyer, A. Swami, 18th International Conference on Very Large Data Bases, Vancouver, Canada, 14 pgs., Aug. 1992.
“SPRINT: A Scalable Parallel Classifier for Data Mining,” J. Shafer, R. Agrawal, M. Mehta, 22nd International Conference on Very Large Data Bases, Bombay, India, pp. 544-555, Sep. 1996.
“Fast Approach for Association Rule Mining for Remotely Sensed Imagery,” Q. Zhou, Q. Ding, W. Perrizo, Proceedings of the ISCA International Conference on Computers and Their Applications, New Orleans, Louisiana, 4 pgs., Mar. 2000.
“Automatic Subspace Clustering of High Dimensional Data for Data Mining Application,” R. Agrawal, J. Cehrke, D. Gunopulos, P. Raghavan, Proceedings of ACM SIGMOD International Conference on Management of Data, Seattle, Washington, 12 pgs., Jun. 1998.
“Efficient and Effective Clustering Method for Spatial Data Mining,” R. Ng, J. Han, Proceedings of the 20th International Conference on Very Large Data Bases, Santiago, Chile, 12 pgs., Sep. 1994.
“Constraint-Based Clustering in Large Databases,” A.K.H. Tung, J. Han, L.V.S. Lakshmanan, R.T. Ng, The 8th International Conference on Database Theory, London, United Kingdom, 15 pgs., Jan. 2001.
“Data Mining: An Overview from a Database Perspective,” M.S. Chen, J. Han, P.S. Yu, IEEE Transactions on Knowledge and Data Engineering, vol. 8, No. 6, pp. 1-40, Dec. 1996.

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