System for providing data analysis services using a support vector machine for processing data received from a remote source

• US 7,797,257 B2
• Filed: 10/29/2007
• Issued: 09/14/2010
• Est. Priority Date: 05/01/1998
• Status: Expired due to Fees

• Current Assignee: Curtis Anderson, Health Discovery Corporation, James Roberts, Joe Mckenzie, Jules B. Paderewski, Julian N. Stern, Memorial Health Systems Incorporated, Timothy P. O'Hayer
• Original Assignee: Health Discovery Corporation
• Inventors: Barnhill, Stephen, Guyon, Isabelle, Weston, Jason
• Primary Examiner(s): HOLMES, MICHAEL B
• Application Number:
  US11/926,129
• Publication Number:
  US 20080059392A1
• Time in Patent Office: 1,051 Days
• Field of Search: 706/13
• US Class Current: 706/13
• CPC Class Codes: G06F 18/211 Selection of the most significant subset of features
• CPC Class Codes: G06F 18/2113 by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
• CPC Class Codes: G06F 18/2115 by evaluating different subsets according to an optimisation criterion, e.g. class separability, forward selection or backward elimination
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06F 18/2411 based on the proximity to a decision surface, e.g. support vector machines
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/10 using kernel methods, e.g. support vector machines [SVM]
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06V 10/764 using classification, e.g. of video objects
• CPC Class Codes: G06V 10/771 Feature selection, e.g. selecting representative features from a multi-dimensional feature space
• CPC Class Codes: G06V 10/774 Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
• CPC Class Codes: G16B 40/20 Supervised data analysis
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16H 10/40 for data related to laboratory analysis, e.g. patient specimen analysis
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A computer system for performing data analysis services using a support vector machine for analyzing data received from a remote source on a distributed network includes a server in communication with the distributed network for receiving a data set and a financial account identifier associated with the remote source. The server communicates over the distributed network with a financial institution to receive funds from a financial account identified by the financial account identifier. A processor receives one or more data sets from the remote source and pre-processes the data to enhance meaning within the data set. The pre-processed data is used to train and test a support vector machine for recognizing patterns within the data. Live data is processed using the trained and tested support vector machine to generate an output which is transmitted to the remote source after the server confirms that payment for the data processing service has been received.

Claims

1. A computer system for providing data analysis services using a support vector machine for analyzing data received from a remote source, the system comprising:

a server in communication with a distributed network for receiving a data set and a financial account identifier from a remote source, the remote source also in communication with the distributed network, wherein the server is further operable for communicating with a financial institution in order to receive funds from a financial account identified by the financial account identifier;

one or more storage devices in communication with the server for storing the data set;

a processor for executing a support vector machine, the processor further operable for;

collecting the data set from the one or more storage devices;

pre-processing the data set to enhance meaning within the data set, wherein meaning is enhanced by one or more of cleaning the data, transforming the data and expanding the data;

before or after pre-processing the data set, dividing the pre-processed data set into a training set and a test set;

processing the training set using the support vector machine so as to train the support vector machine;

in response to training of the support vector machine, processing the test data set using the trained support vector machine in order to test the support vector machine;

in response to receiving a test output from the trained support vector machine indicating that an optimal solution was achieved, collecting a live data set;

pre-processing the live data set to enhance meaning within the live data set;

inputting the live data set into the tested and trained support vector machine to produce a live output comprising a recognized pattern within the live data set;

post-processing the live output to generate an alphanumerical classifier corresponding to the recognized pattern; and

transmitting the alphanumerical classifier to the server;

wherein the server is further operable for transmitting the alphanumerical classifier to the remote source or another remote source after ensuring that funds from the financial account have been secured.

2. The system of claim 1, wherein the financial institution is a bank.

3. The system of claim 1, wherein the financial institution is a credit card company.

4. The system of claim 1, wherein the remote source is a retailer and the data set comprises inventory and audit data.

5. The system of claim 1, wherein the remote source is a medical laboratory and the data set comprises medical data.

6. The system of claim 1, further comprising a firewall disposed between the server and the processor.

7. The system of claim 1, wherein the support vector machine performs recursive feature elimination on the training data and the test data to identify a subset of determinative features within a large number of features that describe the data set, and wherein the processor is further operable for generating a ranked listing of determinative features.

8. A computer system for providing data analysis services over a distributed network, the system comprising:

a remote source in communication with the distributed network;

a server in communication with the distributed network for receiving a data set and a financial account identifier from the remote source, wherein the server is further operable for communicating with a financial institution over the distributed network in order to receive funds from a financial account identified by the financial account identifier;

one or more storage devices in communication with the server for storing the data set;

a processor for executing a support vector machine, the processor further operable for;

collecting the data set from the one or more storage devices;

pre-processing the data set to enhance meaning within the data set, wherein meaning is enhanced by one or more of cleaning the data, transforming the data and expanding the data;

before or after pre-processing the data set, dividing the pre-processed data set into a training set and a test set;

processing the training set using the support vector machine so as to train the support vector machine;

in response to training of the support vector machine, processing the test data set using the trained support vector machine in order to test the support vector machine;

in response to receiving a test output from the trained support vector machine indicating that an optimal solution was achieved, collecting a live data set;

pre-processing the live data set to enhance meaning within the live data set;

inputting the live data set into the tested and trained support vector machine to produce a live output comprising a recognized pattern within the live data set; and

transmitting the recognized pattern to the server;

wherein the server is further operable for transmitting the recognized pattern to the remote source or another remote source after ensuring that funds from the financial account have been secured.

9. The system of claim 8, wherein the financial institution is a bank.

10. The system of claim 8, wherein the financial institution is a credit card company.

11. The system of claim 8, wherein the remote source is a retailer and the data set comprises inventory and audit data.

12. The system of claim 8, wherein the remote source is a medical laboratory and the data set comprises medical data.

13. The system of claim 8, further comprising a firewall disposed between the server and the processor.

14. The system of claim 8, wherein the support vector machine performs recursive feature elimination on the training data and the test data to identify a subset of determinative features within a large number of features that describe the data set, and wherein the processor is further operable for generating a ranked listing of determinative features.