Christopher W Harris

US Patent:

7386527, Jun 10, 2008

Filed:

Apr 10, 2003

Appl. No.:

10/412163

Inventors:

Christopher K. Harris - San Diego CA, US
Mauritius A. R. Schmidtler - Escondido CA, US

Assignee:

Kofax, Inc. - Irvine CA

International Classification:

G06F 17/00
G06F 15/18
G06N 7/00
G06N 7/08
G06N 5/00

US Classification:

706 59, 706 12, 706 45

Abstract:

An improved method of classifying examples into multiple categories using a binary support vector machine (SVM) algorithm. In one preferred embodiment, the method includes the following steps: storing a plurality of user-defined categories in a memory of a computer; analyzing a plurality of training examples for each category so as to identify one or more features associated with each category; calculating at least one feature vector for each of the examples; transforming each of the at least one feature vectors so as reflect information about all of the training examples; and building a SVM classifier for each one of the plurality of categories, wherein the process of building a SVM classifier further includes: assigning each of the examples in a first category to a first class and all other examples belonging to other categories to a second class, wherein if any one of the examples belongs to another category as well as the first category, such examples are assigned to the first class only; optimizing at least one tunable parameter of a SVM classifier for the first category, wherein the SVM classifier is trained using the first and second classes; and optimizing a function that converts the output of the binary SVM classifier into a probability of category membership.

US Patent:

7533076, May 12, 2009

Filed:

Mar 17, 2008

Appl. No.:

12/050096

Inventors:

Christopher K. Harris - San Diego CA, US
Mauritius A. R. Schmidtler - Escondido CA, US

Assignee:

Kofax, Inc. - Irvine CA

International Classification:

G06F 17/00
G06N 7/00
G06F 15/18
G06N 7/08
G06N 5/00

US Classification:

706 59, 706 12, 706 45

Abstract:

An improved method of classifying examples into multiple categories using a binary support vector machine (SVM) algorithm. In one preferred embodiment, the method includes the following steps: storing a plurality of user-defined categories in a memory of a computer, analyzing a plurality of training examples for each category so as to identify one or more features associated with each category; calculating at least one feature vector for each of the examples; transforming each of the at least one feature vectors so as reflect information about all of the training examples; and building a SVM classifier for each one of the plurality of categories, wherein the process of building a SVM classifier further includes: assigning each of the examples in a first category to a first class and all other examples belonging to other categories to a second class, wherein if anyone of the examples belongs to another category as well as the first category, such examples are assigned to the first class only, optimizing at least one tunable parameter of a SVM classifier for the first category, wherein the SVM classifier is trained using the first and second classes; and optimizing a function that converts the output of the binary SVM classifier into a probability of category membership.

US Patent:

7761391, Jul 20, 2010

Filed:

May 23, 2007

Appl. No.:

11/752634

Inventors:

Mauritius A. R. Schmidtler - Escondido CA, US
Christopher K. Harris - San Diego CA, US

Assignee:

Kofax, Inc. - Irvine CA

International Classification:

G06N 5/00

US Classification:

706 12, 706 45

Abstract:

A system, method, data processing apparatus, and article of manufacture are provided for classifying data. Labeled data points are received, each of the labeled data points having at least one label indicating whether the data point is a training example for data points for being included in a designated category or a training example for data points being excluded from a designated category; receiving unlabeled data points; receiving at least one predetermined cost factor of the labeled data points and unlabeled data points; training a transductive classifier using MED through iterative calculation using the at least one cost factor and the labeled data points and the unlabeled data points as training examples; applying the trained classifier to classify at least one of the unlabeled data points, the labeled data points, and input data points; and outputting a classification of the classified data points, or derivative thereof.

US Patent:

8374977, Feb 12, 2013

Filed:

Mar 10, 2010

Appl. No.:

12/721393

Inventors:

Mauritius A. R. Schmidtler - Escondido CA, US
Christopher K. Harris - San Diego CA, US

Assignee:

Kofax, Inc. - Irvine CA

International Classification:

G06N 5/00

US Classification:

706 12, 706 45

Abstract:

A system, method, data processing apparatus, and article of manufacture are provided for classifying data. Labeled data points are received, each of the labeled data points having at least one label indicating whether the data point is a training example for data points for being included in a designated category or a training example for data points being excluded from a designated category; receiving unlabeled data points; receiving at least one predetermined cost factor of the labeled data points and unlabeled data points; training a transductive classifier using MED through iterative calculation using the at least one cost factor and the labeled data points and the unlabeled data points as training examples; applying the trained classifier to classify at least one of the unlabeled data points, the labeled data points, and input data points; and outputting a classification of the classified data points, or derivative thereof.

US Patent:

8438386, May 7, 2013

Filed:

Feb 21, 2010

Appl. No.:

12/709504

Inventors:

Ron Hegli - San Diego CA, US
Hal Lonas - Carlsbad CA, US
Christopher K. Harris - San Diego CA, US

Assignee:

Webroot Inc. - Broomfield CO

International Classification:

H04L 29/06
G06F 17/30
G06F 17/00
G06F 7/04
G06F 15/167
G06F 15/16
G06F 15/173

US Classification:

713166, 713153, 713165, 726 4, 726 11, 726 12, 726 29, 709216, 709217, 709224, 709225

Abstract:

A method and system for controlling access to an Internet resource is disclosed herein. When a request for an Internet resource, such as a Web site, is transmitted by an end-user of a LAN, a security appliance for the LAN analyzes a reputation index for the Internet resource before transmitting the request over the Internet. The reputation index is based on a reputation vector which includes a plurality of factors for the Internet resource such as country of domain registration, country of service hosting, country of an internet protocol address block, age of a domain registration, popularity rank, internet protocol address, number of hosts, to-level domain, a plurality of run-time behaviors, JavaScript block count, picture count, immediate redirect and response latency. If the reputation index for the Internet resource is at or above a threshold value established for the LAN, then access to the Internet resource is permitted. If the reputation index for the Internet resource is below a threshold value established for the LAN, then access to the Internet resource is denied.

US Patent:

20020165717, Nov 7, 2002

Filed:

Apr 8, 2002

Appl. No.:

10/118968

Inventors:

Robert Solmer - San Diego CA, US
Christopher Harris - San Diego CA, US
Mauritius Schmidtler - San Diego CA, US
James Dolter - San Diego CA, US

International Classification:

G10L015/00

US Classification:

704/256000

Abstract:

The invention provides a method and system for extracting information from text documents. A document intake module receives and stores a plurality of text documents for processing, an input format conversion module converts each document into a standard format for processing, an extraction module identifies and extracts desired information from each text document, and an output format conversion module converts the information extracted from each document into a standard output format. These modules operate simultaneously on multiple documents in a pipeline fashion so as to maximize the speed and efficiency of extracting information from the plurality of documents.

US Patent:

20030120653, Jun 26, 2003

Filed:

Oct 7, 2002

Appl. No.:

10/267952

Inventors:

Sean Brady - San Diego CA, US
Christopher Harris - San Diego CA, US
Josh Dammeier - San Diego CA, US
Sameer Samat - San Diego CA, US

International Classification:

G06F007/00

US Classification:

707/007000

Abstract:

An automated method of creating or updating a database, the method comprising, a) entering at least one example document that is relevant to a subject taxonomy in a retrieval priority list, if there is a plurality of example documents stored in the retrieval priority list, ranking the example documents according to the relevancy of the example documents to the subject taxonomy; b) retrieving a document from a network of documents, where the document is the most relevant document to the subject taxonomy stored in the retrieval priority list; c) harvesting information from specified fields of the document; d) classifying the information into one or more classes according to specified categories of the subject taxonomy; e) storing the information into a database; f) determining whether the information are links to other documents; g) ranking the link's according to relevancy to the subject taxonomy, and storing the links in the retrieval priority list according to the relevancy; h) terminating the method, provided the method's stop criteria have been met; and i) repeating steps b) through h), provided the method's stop criteria has not been met.

US Patent:

20050134935, Jun 23, 2005

Filed:

Dec 19, 2003

Appl. No.:

10/742131

Inventors:

Mauritius Schmidtler - Escondido CA, US
Scott Texeira - San Diego CA, US
Christopher Harris - San Diego CA, US
Sameer Samat - San Diego CA, US
Roland Borrey - Villa Park CA, US
Anthony Macciola - Chino Hills CA, US

International Classification:

H04N001/40

US Classification:

358448000, 358450000

Abstract:

A method and system for delineating document boundaries and identifying document types by analyzing digital images of one or more documents, automatically categorizing one or more pages or subdocuments within the one or more documents and automatically generating delineation identifiers, such as computer-generated images of separation pages inserted between digital images belonging to different categories, a description of the categorization sequence of the digital images, or a computer-generated electronic label affixed or associated with said digital images.