Patents by Inventor Sholom M. Weiss

Sholom M. Weiss 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).

  • Publication number: 20160267224
    Abstract: Software that performs the following steps: (i) receiving a first set of observed data pertaining to healthcare events, the first set of observed data including a subset of patient care event data pertaining to patient care events and a subset of prescription data pertaining to prescription events; (ii) generating a graphical model representing a probabilistic relationship between the patient care event data and the prescription data, the graphical model including a set of latent variable(s) estimated from the first set of observed data using an expectation maximization method; (iii) receiving a second set of observed data pertaining to healthcare events associated with a healthcare provider; and (iv) computing, using a dynamic programming approach, a first prescription score for the healthcare provider relating to a computed probability under the generated graphical model of at least one prescription event of the second set of observed data.
    Type: Application
    Filed: March 10, 2015
    Publication date: September 15, 2016
    Inventors: Ramesh Natarajan, Peder A. Olsen, Sholom M. Weiss
  • Patent number: 8793106
    Abstract: A system, method and computer program product for predicting at least one feature of at least one product being manufactured. The system receives, from at least one sensor installed in equipment performing one or more manufacturing process steps, at least one measurement of the feature of the product being manufactured. The system selects one or more of the received measurement of the feature of the product. The system estimates additional measurements of the feature of the product at a current manufacturing process step. The system creates a computational model for predicting future measurements of the feature of the product, based on the selected measurement and the estimated additional measurements. The system predicts the future measurements of the feature of the product based on the created computational model. The system outputs the predicted future measurements of the feature of the product.
    Type: Grant
    Filed: September 23, 2011
    Date of Patent: July 29, 2014
    Assignee: International Business Machines Corporation
    Inventors: Robert J. Baseman, Amit Dhurandhar, Sholom M. Weiss, Brian F. White
  • Patent number: 8594821
    Abstract: A system, a method and a computer program product for identifying incompatible manufacturing tools. The system receives measurements of products that were subject to a manufacturing process involving a plurality of manufacturing tools. The measurements pertain to a performance characteristic of each product. The system evaluates whether each manufacturing tool implemented in a sequential manufacturing process individually performs normally based on the received measurements. In response to evaluating each manufacturing tool implemented in said manufacturing process individually performs normally, the system evaluates whether a first combination of the manufacturing tools together in sequential manufacturing process perform normally based on the received measurements.
    Type: Grant
    Filed: February 18, 2011
    Date of Patent: November 26, 2013
    Assignee: International Business Machines Corporation
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Patent number: 8533635
    Abstract: The present invention includes a computing system determining a best alias rule in a semiconductor manufacturing process. The computing system obtains an original rule and candidate alias rules based on sampled data from the semiconductor manufacturing process. The computing system compares the original rule to the candidate alias rules. The computing system ranks the candidate alias rules according to the comparison. The computing system filters the ranked candidate alias rules. A user selects one rule among the filtered candidate alias rules based on knowledge of the semiconductor manufacturing process.
    Type: Grant
    Filed: January 20, 2010
    Date of Patent: September 10, 2013
    Assignee: International Business Machines Corporation
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Publication number: 20130080125
    Abstract: A system, method and computer program product for predicting at least one feature of at least one product being manufactured. The system receives, from at least one sensor installed in equipment performing one or more manufacturing process steps, at least one measurement of the feature of the product being manufactured. The system selects one or more of the received measurement of the feature of the product. The system estimates additional measurements of the feature of the product at a current manufacturing process step. The system creates a computational model for predicting future measurements of the feature of the product, based on the selected measurement and the estimated additional measurements. The system predicts the future measurements of the feature of the product based on the created computational model. The system outputs the predicted future measurements of the feature of the product.
    Type: Application
    Filed: September 23, 2011
    Publication date: March 28, 2013
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Robert J. Baseman, Amit Dhurandhar, Sholom M. Weiss, Brian F. White
  • Publication number: 20120215335
    Abstract: A system, a method and a computer program product for identifying incompatible manufacturing tools. The system receives measurements of products that were subject to a manufacturing process involving a plurality of manufacturing tools. The measurements pertain to a performance characteristic of each product. The system evaluates whether each manufacturing tool implemented in a sequential manufacturing process individually performs normally based on the received measurements. In response to evaluating each manufacturing tool implemented in said manufacturing process individually performs normally, the system evaluates whether a first combination of the manufacturing tools together in sequential manufacturing process perform normally based on the received measurements.
    Type: Application
    Filed: February 18, 2011
    Publication date: August 23, 2012
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Publication number: 20110178624
    Abstract: The present invention includes a computing system determining a best alias rule in a semiconductor manufacturing process. The computing system obtains an original rule and candidate alias rules based on sampled data from the semiconductor manufacturing process. The computing system compares the original rule to the candidate alias rules. The computing system ranks the candidate alias rules according to the comparison. The computing system filters the ranked candidate alias rules. A user selects one rule among the filtered candidate alias rules based on knowledge of the semiconductor manufacturing process.
    Type: Application
    Filed: January 20, 2010
    Publication date: July 21, 2011
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Patent number: 7650251
    Abstract: A fabrication history a group of wafers is provided, having a record for each wafer of the manufacturing events that did or did not occur in its fabrication, and having the measured value of a given target. A binary decision rule is formed based on the fabrication history, the rule being that if a wafer has a particular pattern of manufacturing events in its fabrication history then the statistic of the given fabrication target for that wafer is a first value; otherwise, the statistic is a second value having at least a given distance from the first value. The pattern of manufacturing events in the binary decision rule is identified in the generation of the binary decision rule. The identified pattern is significant with respect to the given target.
    Type: Grant
    Filed: December 12, 2008
    Date of Patent: January 19, 2010
    Assignee: International Business Machines Corporation
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Patent number: 7539585
    Abstract: A fabrication history of a group of wafers is provided, having a record for each wafer of the manufacturing events that did or did not occur in its fabrication, and having the measured value of a given target. A binary decision rule is formed based on the fabrication history, the rule being that if a wafer has a particular pattern of manufacturing events in its fabrication history then the statistic of the given fabrication target for that wafer is a first value; otherwise, the statistic is a second value having at least a given distance from the first value. The pattern of manufacturing events in the binary decision rule is identified in the generation of the binary decision rule. The identified pattern is significant with respect to the given target.
    Type: Grant
    Filed: June 14, 2007
    Date of Patent: May 26, 2009
    Assignee: International Business Machines Corporation
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Publication number: 20090093904
    Abstract: A fabrication history a group of wafers is provided, having a record for each wafer of the manufacturing events that did or did not occur in its fabrication, and having the measured value of a given target. A binary decision rule is formed based on the fabrication history, the rule being that if a wafer has a particular pattern of manufacturing events in its fabrication history then the statistic of the given fabrication target for that wafer is a first value; otherwise, the statistic is a second value having at least a given distance from the first value. The pattern of manufacturing events in the binary decision rule is identified in the generation of the binary decision rule. The identified pattern is significant with respect to the given target.
    Type: Application
    Filed: December 12, 2008
    Publication date: April 9, 2009
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Publication number: 20080312858
    Abstract: A fabrication history of a group of wafers is provided, having a record for each wafer of the manufacturing events that did or did not occur in its fabrication, and having the measured value of a given target. A binary decision rule is formed based on the fabrication history, the rule being that if a wafer has a particular pattern of manufacturing events in its fabrication history then the statistic of the given fabrication target for that wafer is a first value; otherwise, the statistic is a second value having at least a given distance from the first value. The pattern of manufacturing events in the binary decision rule is identified in the generation of the binary decision rule. The identified pattern is significant with respect to the given target.
    Type: Application
    Filed: June 14, 2007
    Publication date: December 18, 2008
    Inventors: Robert J. Baseman, Fateh A. Tipu, Sholom M. Weiss
  • Patent number: 6654739
    Abstract: A procedure for clustering documents that operates in high dimensions, processes tens of thousands of documents and groups them into several thousand clusters or, by varying a single parameter, into a few dozen clusters. The procedure is specified in two parts: computing a similarity score representing the k most similar documents (typically the top ten) for each document in the collection, and grouping the documents into clusters using the similarly scores.
    Type: Grant
    Filed: January 31, 2000
    Date of Patent: November 25, 2003
    Assignee: International Business Machines Corporation
    Inventors: Chidanand Apte, Sholom M. Weiss, Brian F. White
  • Publication number: 20030033436
    Abstract: A pattern recognition method induces ensembles of decision rules from data regression problems. Instead of direct prediction of a continuous output variable, the method discretizes the variable by k-means clustering and solves the resultant classification problem. Predictions on new examples are made by averaging the mean values of classes with votes that are close in number to the most likely class.
    Type: Application
    Filed: May 14, 2001
    Publication date: February 13, 2003
    Inventor: Sholom M. Weiss
  • Patent number: 6286000
    Abstract: A lightweight document matcher employs minimal processing and storage. The lightweight document matcher matches new documents to those stored in a database. The matcher lists, in order, those stored documents that are most similar to the new document. The new documents are typically problem statements or queries, and the stored documents are potential solutions such as FAQs (Frequently Asked Questions). Given a set of documents, titles, and possibly keywords, an automatic back-end process constructs a global dictionary of unique keywords and local dictionaries of relevant words for each document. The application front-end uses this information to score the relevance of stored documents to new documents. The scoring algorithm uses the count of matched words as a base score, and then assigns bonuses to words that have high predictive value. It optionally assigns an extra bonus for a match of words in special sections, e.g., titles.
    Type: Grant
    Filed: December 1, 1998
    Date of Patent: September 4, 2001
    Assignee: International Business Machines Corporation
    Inventors: Chidanand Apte, Frederick J. Damerau, Sholom M. Weiss, Brian F. White
  • Patent number: 6253169
    Abstract: A text categorization method automatically classifies electronic documents by developing a single pooled dictionary of words for a sample set of documents, and then generating a decision tree model, based on the pooled dictionary, for classifying new documents. Adaptive resampling techniques are applied to improve the accuracy of the decision tree model.
    Type: Grant
    Filed: May 28, 1998
    Date of Patent: June 26, 2001
    Assignee: International Business Machines Corporation
    Inventors: Chidanand Apte, Frederick J. Damerau, Sholom M. Weiss
  • Patent number: 5724263
    Abstract: A facility is provided for enhancing an operations support system so that, based on data generated as a result of an event occurring in an associated telecommunications network, the operations support system can predict the likelihood of the event occurring again in the network.
    Type: Grant
    Filed: May 30, 1997
    Date of Patent: March 3, 1998
    Assignee: AT&T Corp
    Inventors: Sasisekharan Raguram, V. Seshadri, Sholom M. Weiss