Method and apparatus for data mining to discover...

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

Reexamination Certificate

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C707S793000, C707S793000, C707S793000, C707S793000, C707S793000

Reexamination Certificate

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07043476

ABSTRACT:
Data mining techniques are provided which are effective and efficient for discovering useful information from an amorphous collection or data set of records. For example, the present invention provides for the mining of data, e.g., of several or many records, to discover interesting associations between entries of qualitative text, and covariances between data of quantitative numerical types, in records. Although not limited thereto, the invention has particular application and advantage when the data is of a type such as clinical, pharmacogenomic, forensic, police and financial records, which are characterized by many varied entries, since the problem is then said to be one of “high dimensionality” which has posed mathematical and technical difficulties for researchers. This is especially true when considering strong negative associations and negative covariance, i.e., between items of data which may so rarely come together that their concurrence is never seen in any record, yet the fact that this is not expected is of potential great interest.

REFERENCES:
Muqattash et al., APplication of Data Mining and Mathematical Analysis to the Zeta Function and the Riemann Hypothesis, Ursinus College Department of Mathematics and Computer Science, Nov. 2004, pp. 1-65.
Bohigas et al., What's Happenning in the Mathematical Sciences, Lecture Notes in Physics, vol. 209, 1994, pp. 2-17.
Borwein et al., Searching Symbolically for Apery-Like Formulae for values of the Rieman Zeta Function, ACM Sigsam Bulletin, vol. 30, Issue 2, Jnes 1996, pp. 2-7.
Mannila, Theoretical Frameworks for Data Mining, SIGKDD Explorations, vol. 1, Issue 2, Jan. 2000, pp. 30-32.
Alstrup et al., Pattern Matching in Dynamic Texts, pp. 819-828.
Skorobogatovet al., On the Decoding of Algebraic-Geometric Codes, IEEE, 1990, pp. 1051-1060.
Demillo, Social Process and Proofs of Theorems and Programs, Mc Graw-Hill 1953, p. 206-214.
While et al., An Implementation of Parallel Pattern-Maching via Concurrent Hakell, Australian Computer Society Inc., 2001, pp. 293-302.
Karim K Hirji, Exploring Data Mining Implementation, Communication of the ACM, Jul. 2001, vol. 44, No. 7, pp. 87-93.
J. Garnier et al., “Analysis of the Accuracy and Implications of Simple Methods for Predicting the Secondary Structure of Globular Proteins,” J. Mol. Biol., 120, pp. 97-120, 1978.
B. Robson et al., “Refined Models for Computer Calculations in Protein Engineering—Calculation and Testing of Atomic Potential Functions Compatible with More Efficient Calculations,” J. Mol. Biol., 188, pp. 259-281, 1986.
B. Robson, “Studies in the Assessment of Folding Quality for Protein Modeling and Structure Prediction,” Journal of Proteome Research, vol. 1, No. 2, pp. 115-133, 2002.
T. Bayes, “An Essay Towards Solving a Problem in the Doctrine of Chances,” Phil. Trans. Roy. Soc. Ser. B, 53, pp. 370-403, 1763.
H.H. Goode, “Recent Developments in Information and Decision Processes,” Machol & Grey, Rds., pp. 71-91, 1962.
R. Pain et al., “Analysis of the Code Relating Sequence to Conformation in Globular Proteins,” vol. 227, pp. 62-63, 1970.
S.S. Wilks, Mathematical Statistics, Section 7.7, pp. 177-182, 1962.
J. Garnier et al., “The GOR Method for Predicting Secondary Structures in Proteins,” ‘Prediction of Protein Structure and the Principles of Protein Conformation,’ Ed. G.D. Fasman, pp. 417-465, 1989.
J. Garnier et al., “GOR Method for Predicting Protein Secondary Structure from Amino Acid Sequence,” Methods in Enzymology, vol. 266, ‘Computer Methods for Macromolecular Sequency Analysis,’ Ed. R.F. Dolittle, pp. 540-553, 1996.
B. Robson, “Analysis of the Code Relating Sequence to Conformation in Globular Proteins: Theory and Application of Expected Information,” Biochem. J. 151, pp. 853-867, 1974.
B. Robson, “Fastfinger: A Study into the Use of Compressed Residue Pair Separation Matrices for Protein Sequence Comparison,” IBM Systems Journal, vol. 40, No. 2, pp. 442-463, 2001.

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