Patents by Inventor Claudia Perlich
Claudia Perlich 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: 11100411Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: GrantFiled: May 25, 2017Date of Patent: August 24, 2021Assignee: International Business Machines CorporationInventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Publication number: 20170262759Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: ApplicationFiled: May 25, 2017Publication date: September 14, 2017Inventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Patent number: 9684868Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: GrantFiled: May 7, 2015Date of Patent: June 20, 2017Assignee: International Business Machines CorporationInventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Publication number: 20150235137Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: ApplicationFiled: May 7, 2015Publication date: August 20, 2015Inventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Patent number: 9031888Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: GrantFiled: August 10, 2011Date of Patent: May 12, 2015Assignee: International Business Machines CorporationInventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Publication number: 20130041860Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.Type: ApplicationFiled: August 10, 2011Publication date: February 14, 2013Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Richard D. Lawrence, Estepan Meliksetian, Prem Melville, Claudia Perlich, Karthik Subbian
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Publication number: 20110251877Abstract: A model for impact analysis determines impact of part removal from a product. An entity is identifies that includes a plurality of sub-components. One or more performance measures associated with the entity are identified. One or more of the sub-components to be removed from the entity are identified. A substitution impact function is defined. Impact on said one or more performance measures is determined using the substitution impact function.Type: ApplicationFiled: April 7, 2010Publication date: October 13, 2011Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Richard D. Lawrence, Claudia Perlich
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Publication number: 20080208788Abstract: A method (and system) of predicting an unobserved target variable includes building a graphical predictive model from domain knowledge, which takes advantage of conditional independence to facilitate inference about the unobserved target variable, given observations of other variables in the graphical predictive model from a plurality of information sources.Type: ApplicationFiled: February 27, 2007Publication date: August 28, 2008Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Srujana Merugu, Claudia Perlich, Saharon Rosset