Patents by Inventor Salahuddin Ahmed
Salahuddin Ahmed has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 7693704Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: GrantFiled: February 14, 2005Date of Patent: April 6, 2010Assignee: Lexis-Nexis Group, a division of Reed Elsevier Inc.Inventors: Timothy L. Humphrey, Xin Allan Lu, Afsar Parhizgar, Salahuddin Ahmed, James S. Wiltshire, Jr., John T. Morelock, Joseph P. Harmon, Spiro G. Collias, Paul Zhang
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Patent number: 7464025Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: GrantFiled: February 14, 2005Date of Patent: December 9, 2008Assignee: Lexis-Nexis GroupInventors: Timothy L. Humphrey, Xin Allan Lu, Afsar Parhizgar, Salahuddin Ahmed, James S. Wiltshire, Jr., John T. Morelock, Joseph P. Harmon, Spiro G. Collias, Paul Zhang
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Publication number: 20050149524Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: ApplicationFiled: February 14, 2005Publication date: July 7, 2005Inventors: Timothy Humphrey, Xin Lu, Afsar Parhizgar, Salahuddin Ahmed, James Wiltshire, John Morelock, Joseph Harmon, Spiro Collias, Paul Zhang
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Publication number: 20050149523Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: ApplicationFiled: February 14, 2005Publication date: July 7, 2005Inventors: Timothy Humphrey, Xin Lu, Afsar Parhizgar, Salahuddin Ahmed, James Wiltshire, John Morelock, Joseph Harmon, Spiro Collias, Paul Zhang
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Publication number: 20050144169Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: ApplicationFiled: February 14, 2005Publication date: June 30, 2005Inventors: Timothy Humphrey, Xin Lu, Afsar Parhizgar, Salahuddin Ahmed, James Wiltshire, John Morelock, Joseph Harmon, Spiro Collias, Paul Zhang
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Patent number: 6856988Abstract: A computer-automated system and method identify text in a first “citing” court case, near a “citing instance” (in which a second “cited” court case is cited), that indicates the reason(s) for citing (RFC). The automated method of designating text, taken from a set of citing documents, as reasons for citing (RFC) that are associated with respective citing instances of a cited document, has steps including: obtaining contexts of the citing instances in the respective citing documents (each context including text that includes the citing instance and text that is near the citing instance), analyzing the content of the contexts, and selecting (from the citing instances' context) text that constitutes the RFC, based on the analyzed content of the contexts. A related computer-automated system and method selects content words that are highly related to the reasons a particular document is cited, and gives them weights that indicate their relative relevance.Type: GrantFiled: December 21, 1999Date of Patent: February 15, 2005Assignee: Lexis-Nexis GroupInventors: Timothy L. Humphrey, Xin Allan Lu, Afsar Parhizgar, Salahuddin Ahmed, James S. Wiltshire, Jr., John T. Morelock, Joseph P. Harmon, Spiro G. Collias, Paul Zhang
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Patent number: 6772149Abstract: A computer-implemented method of gathering large quantities of training data from case law documents (especially suitable for use as input to a learning algorithm that is used in a subsequent process of recognizing and distinguishing fact passages and discussion passages in additional case law documents) has steps of: partitioning text in the documents by headings in the documents, comparing the headings in the documents to fact headings in a fact heading list and to discussion headings in a discussion heading list, filtering from the documents the headings and text that is associated with the headings, and storing (on persistent storage in a manner adapted for input into the learning algorithm) fact training data and discussion training data that are based on the filtered headings and the associated text.Type: GrantFiled: September 23, 1999Date of Patent: August 3, 2004Assignee: Lexis-Nexis GroupInventors: John T. Morelock, James S. Wiltshire, Jr., Salahuddin Ahmed, Timothy Lee Humphrey, Xin Allan Lu
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Patent number: 6684202Abstract: A system and method for binary classification of text units such as sentences, paragraphs and documents as either a rule of law (ROL) or not a rule of law (˜ROL). During a training phase of the system and method of the present invention, an initialized knowledge base and labeled or pre-classified sentences are used to build a trained knowledge base. The trained knowledge base contains an equation, a threshold, and a plurality of statistical values called Z values. When inputting text documents for classification, a Z value is generated for each term or token in the input text. The Z values are input to the equation which calculates a score for each sentence. Each calculated score is then compared to the threshold to classify each sentence as either ROL or ˜ROL.Type: GrantFiled: May 31, 2000Date of Patent: January 27, 2004Assignee: Lexis NexisInventors: Timothy L. Humphrey, X. Allan Lu, James S. Wiltshire, Jr., John T. Morelock, Spiro G. Collias, Salahuddin Ahmed
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Patent number: 6502081Abstract: An economic, scalable machine learning system and process perform document (concept) classification with high accuracy using large topic schemes, including large hierarchical topic schemes. One or more highly relevant classification topics is suggested for a-given document (concept) to be classified. The invention includes training and concept classification processes. The invention also provides methods that may be used as part of the training and/or concept classification processes, including: a method of scoring the relevance of features in training concepts, a method of ranking concepts based on relevance score, and a method of voting on topics associated with an input concept. In a preferred embodiment, the invention is applied to the legal (case law) domain, classifying legal concepts (rules of law) according to a proprietary legal topic classification scheme (a hierarchical scheme of areas of law).Type: GrantFiled: August 4, 2000Date of Patent: December 31, 2002Assignee: Lexis NexisInventors: James S. Wiltshire, Jr., John T. Morelock, Timothy L. Humphrey, X. Allan Lu, James M. Peck, Salahuddin Ahmed