Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2004-04-16
2010-06-01
Sparks, Donald (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
C703S022000, C705S007380, C705S014270
Reexamination Certificate
active
07730003
ABSTRACT:
Models are generated using a variety of tools and features of a model generation platform. For example, in connection with a project in which a user generates a predictive model based on historical data about a system being modeled, the user is provided through a graphical user interface a structured sequence of model generation activities to be followed, the sequence including dimension reduction, model generation, model process validation, and model re-generation.Historical multi-dimensional data is received representing multiple source variables to be used as an input to a predictive model of a commercial system and applying transformations to the data that are selected based on the strength of measurement represented by a variable; variables are transformed into new more predictive variables, including the Bayesian renormalization of sparsely sampled variable and including the imputation of missing values for categorical or continuous variables.
REFERENCES:
patent: 5491629 (1996-02-01), Fox et al.
patent: 5583763 (1996-12-01), Atcheson et al.
patent: 5592560 (1997-01-01), Deaton et al.
patent: 5621812 (1997-04-01), Deaton et al.
patent: 5692107 (1997-11-01), Simoudis et al.
patent: 5701400 (1997-12-01), Amado
patent: 5826250 (1998-10-01), Trefler
patent: 6026397 (2000-02-01), Sheppard
patent: 6185543 (2001-02-01), Galperin et al.
patent: 6269325 (2001-07-01), Lee et al.
patent: 6317752 (2001-11-01), Lee et al.
patent: 6321205 (2001-11-01), Eder
patent: 6381504 (2002-04-01), Havener et al.
patent: 6430539 (2002-08-01), Lazarus et al.
patent: 6542894 (2003-04-01), Lee et al.
patent: 6556977 (2003-04-01), Lapointe et al.
patent: 6567812 (2003-05-01), Garrecht et al.
patent: 6631360 (2003-10-01), Cook
patent: 6640215 (2003-10-01), Galperin et al.
patent: 6684208 (2004-01-01), Kil et al.
patent: 6687696 (2004-02-01), Hofmann et al.
patent: 6782390 (2004-08-01), Lee et al.
patent: 6807535 (2004-10-01), Goodkovsky
patent: 6836773 (2004-12-01), Tamayo et al.
patent: 6839682 (2005-01-01), Blume et al.
patent: 6859529 (2005-02-01), Duncan et al.
patent: 6879971 (2005-04-01), Keeler et al.
patent: 6954758 (2005-10-01), O'Flaherty
patent: 6956941 (2005-10-01), Duncan et al.
patent: 7043461 (2006-05-01), Kedher et al.
patent: 7047251 (2006-05-01), Reed et al.
patent: 7349827 (2008-03-01), Heller et
patent: 7499897 (2009-03-01), Pinto et al.
patent: 7562058 (2009-07-01), Pinto et al.
patent: 2002/0052836 (2002-05-01), Galperin et al.
patent: 2002/0123923 (2002-09-01), Manganaris et al.
patent: 2002/0127529 (2002-09-01), Cassato et al.
patent: 2003/0004777 (2003-01-01), Phillips
patent: 2003/0018601 (2003-01-01), Lee et al.
patent: 2003/0088565 (2003-05-01), Walter et al.
patent: 2003/0154442 (2003-08-01), Papierniak
patent: 2003/0212678 (2003-11-01), Bloom et al.
patent: 2004/0002833 (2004-01-01), Tang et al.
patent: 2004/0030667 (2004-02-01), Xu et al.
patent: 2004/0111314 (2004-06-01), Cavaretta
patent: 2005/0004786 (2005-01-01), Thomason
patent: 2005/0089768 (2005-04-01), Tanaka et al.
patent: 2005/0096950 (2005-05-01), Caplan et al.
patent: 2005/0234688 (2005-10-01), Pinto et al.
patent: 2005/0234753 (2005-10-01), Pinto et al.
patent: 2005/0234760 (2005-10-01), Pinto et al.
patent: 2005/0234761 (2005-10-01), Pinto et al.
patent: 2005/0234762 (2005-10-01), Pinto et al.
patent: 2006/0161403 (2006-07-01), Jiang et al.
patent: 2010/0010878 (2010-01-01), Pinto et al.
patent: 2241119 (2002-03-01), None
patent: 1085429 (2001-03-01), None
patent: WO 99/22328 (1999-05-01), None
patent: WO 02/19061 (2002-03-01), None
patent: WO 03/005232 (2003-01-01), None
patent: PCT/US2005/011749 (2006-02-01), None
Harrison, H.C., “An Intelligent Business Forecasting System,” ACM May 1993, pp. 229-236.
Haughton et al., “A Review of Software Packages for Data Mining,” The American Statistician, Nov. 2003, vol. 57, No. 5, pp. 290-309.
Angus, Enterprise Miner 5.1 Digs Into Data, InforWorld, Aug. 9, 2004, vol. 26, No. 32, pp. 22- 23.
Chapman et al., CRISP-DM 1.0 Step-by-Step Data Mining Guide, Aug. 2000, pp. 27-31, 53-59, 71-79.
Cabena et al., Intelligent Miner for Data Applications Guide, IBM Redbook, SG24-5252-00, Mar. 1999, pp. 9-17, 27-35, 69-77, 87-108, 111-128.
Schikora et al., Efficacy of End-User Neural Network and Data Mining Software for Predicting Complex System Performance, International Journal of Production Economics, vol. 84, pp. 231-53, Jun. 2003.
Bhattacharyya , Evolutionary Algorithms in Data Mining: Multi-Objective Performance Modeling for Direct Marketing, Proceedings of the Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 465-473, Aug. 2000.
Pearce et al., Experimentation and Self Learning in Continuous Database Marketing, IEEE International Conference on Data Mining, pp. 775-778, Dec. 2002.
Etzion et al., e-CLV: A Modeling Approach for Customer Lifetime Evaluation In e-Commerce Domains, With an Application and Case Study for Online Auctions, IEEE International Conference on e-Technology, e-Commerce and e-Service, pp. 149-156, Mar. 2004.
Commercial software: SPSS Clementine: www/spss.com/Clementine/index.html.
“On-line Seminar: How to keep customers and increase profits using predictive analytics powered by Clementine”, www.spss.com/spssbi/directresponse/clementinewebinar/index.cfm?dcode=d4183.
“SAS Enterprise Miner”, www/sas.com/technologies/analytics/datamining/miner.
SAS JMP, www.jmp.com.
Clifford C. Clogg, et al., “Multiple Imputation of Industry and Occupation Codes in Census Public-Use Samples Using Bayesian Logistic Regression”,Journal of the American Statistical Association, vol. 86, No. 413, pp. 68-78 (Mar. 1991).
Roderick J.A. Little et al.,Statistical Analysis with Missing Data(2ndEdition), John J. Wiley & Sons, Inc., (2002), pp. 19-22; 166-188; and 292-309.
Donald B. Rubin, “Using Empirical Bayes Techniques in the Law School Validity Studies”,Journal of the American Statistical Association, vol. 75, No. 372, pp. 801-816 (Dec. 1980).
U.S. Appl. No. 10/826,452, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims.
U.S. Appl. No. 10/826,711, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims.
U.S. Appl. No. 10/826,949, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims, Declaration and claims charts as filed with PTO on Oct 1, 2007.
U.S. Appl. No. 10/826,624, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims.
U.S. Appl. No. 10/826,630, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims.
U.S. Appl. No. 10/826,947, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims, Declaration and claims charts as filed with PTO on Oct 1, 2007.
U.S. Appl. No. 10/826,453, filed Apr. 16, 2004, PAIR Transaction History, Current Pending Claims.
Declaration filed in related U.S. Appl. No. 10/826,949 filed Apr. 16, 2004 along with claim chart.
Declaration filed in related U.S. Appl. No. 10/826,947 filed Apr. 16, 2004 along with claim chart.
C Bounsaythip, E Rinta-Runsala “Overview of Data Mining for Customer Behavior Modeling”—Finland: VTT Information Technology, Research Report TTE 1-18, 2001.
PAIR Transaction History for U.S. Appl. No. 10/826,452, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,711, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,949, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,624, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,630, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,947, filed on Apr. 16, 2004.
PAIR Transaction History for U.S. Appl. No. 10/826,453, filed on Apr. 16, 2004.
Tashman, “Automatic Forecasting Software: A Survey and Evaluation,”International Journal of Forecasting, 7(2) (1991).
Wang et al., “An Expert System for Forecasting Model Selection,”IEEE(1992).
New technology Card News, 10(6) (Apr. 3, 1995).
Pinto, “Smart Data Use Can Improve
Jacobs Marc
Mansfield Richard
Pinto Stephen K.
Rubin Donald
Bharadwaj Kalpana
Fish & Richardson P.C.
Fortelligent, Inc.
Sparks Donald
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