Patents by Inventor Erick Cantu-Paz
Erick Cantu-Paz 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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Publication number: 20110246286Abstract: Sponsored search advertising utilizes a click probability as one factor in selecting and ranking advertisements that are displayed with search results. The probability of click may also be referred to as a predicted click-through rate (“CTR”) that may be multiplied by an advertiser's bid for a particular advertisement to rank the display of advertisements. An accurate prediction of the click probability improves the potential revenue that is generated by advertisements in a pay per click system. Other advertising systems may benefit from an accurate and reliable estimate for an advertisement's probability of click in different environments and scenarios.Type: ApplicationFiled: April 6, 2010Publication date: October 6, 2011Applicant: Yahoo Inc.Inventors: Ozgur Cetin, Kannan Achan, Erick Cantu-Paz, Rukmini Iyer
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Patent number: 8015502Abstract: The present invention is directed towards systems and methods for providing dynamic search results based upon historical data through the use of one or more widgets. The method of the present invention comprises receiving a request for content from a client and generating one or more widgets for providing search result content. A display profile is applied to the one or more widgets and the one or more widgets are combined with static search results to form a search result page that is provided to a requesting client.Type: GrantFiled: May 22, 2007Date of Patent: September 6, 2011Assignee: Yahoo! Inc.Inventors: Christopher LuVogt, Erick Cantu-Paz
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Publication number: 20110125572Abstract: Search and advertising systems may be optimized through the use of user feedback. Selected parameters such as ranking, filtering, placement, and pricing may be optimized to achieve certain objectives. The optimization may include real-time user monitoring of multiple configurations with various parameters. In one embodiment, a subset of user queries may be assigned to a particular configuration for monitoring and measuring the real-time performance of that configuration. The performance for multiple configurations may be used to identify optimal settings.Type: ApplicationFiled: November 25, 2009Publication date: May 26, 2011Applicant: YAHOO! INC.Inventors: Erick Cantu-Paz, Eren Manavoglu
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Patent number: 7631008Abstract: The present invention is directed towards systems and methods for predicting a frequency with which an advertisement displayed in response to a query will be selected. The method of the present invention comprises receiving analytics data associated with a display of one or more advertisements in response to one or more queries. One or more features associated with the one or more advertisements displayed in response to the one or more queries are identified. One or more functions are generated for predicting a frequency with which a given advertisement displayed in response to a query will be selected using the analytics data and features associated with the one or more advertisements displayed in response to the one or more queries.Type: GrantFiled: June 29, 2006Date of Patent: December 8, 2009Assignee: Yahoo! Inc.Inventors: Chad Carson, Ashvin Kannan, Erick Cantu-Paz, Rukmini Iyer, Pero Subasic, Christopher C. LuVogt, Christopher Leggetter, Jan Pedersen, David Cho-Lun Ku
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Publication number: 20090276729Abstract: The subject matter disclosed herein relates to maintaining a history of user interaction data within a sliding window, where the sliding window may be sized based at least in part on a quantification of such user interaction.Type: ApplicationFiled: April 30, 2008Publication date: November 5, 2009Applicant: Yahoo! Inc.Inventor: Erick Cantu-Paz
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Publication number: 20090157559Abstract: A method of facilitating the endorsement of products through Internet advertisements accepts a bid for an endorsement, enables communication, associated with the bid, between an advertiser and a potential endorser, and serves an endorsement associated with the bid. In one implementation, the endorsement is displayed together with a symbol verifying the endorser.Type: ApplicationFiled: December 17, 2007Publication date: June 18, 2009Applicant: YAHOO! INC.Inventors: Su-Lin Wu, Erick Cantu-Paz, Christopher John Leggetter
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Publication number: 20080295006Abstract: The present invention is directed towards systems and methods for providing dynamic search results based upon historical data through the use of one or more widgets. The method of the present invention comprises receiving a request for content from a client and generating one or more widgets for providing search result content. A display profile is applied to the one or more widgets and the one or more widgets are combined with static search results to form a search result page that is provided to a requesting client.Type: ApplicationFiled: May 22, 2007Publication date: November 27, 2008Inventors: Christopher LuVogt, Erick Cantu-Paz
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Publication number: 20070112840Abstract: The present invention is directed towards systems and methods for predicting a frequency with which an advertisement displayed in response to a query will be selected. The method of the present invention comprises receiving analytics data associated with a display of one or more advertisements in response to one or more queries. One or more features associated with the one or more advertisements displayed in response to the one or more queries are identified. One or more functions are generated for predicting a frequency with which a given advertisement displayed in response to a query will be selected using the analytics data and features associated with the one or more advertisements displayed in response to the one or more queries.Type: ApplicationFiled: June 29, 2006Publication date: May 17, 2007Applicant: Yahoo! Inc.Inventors: Chad Carson, Ashvin Kannan, Erick Cantu-Paz, Rukmini Iyer, Pero Subasic, Christopher LuVogt, Christopher Leggetter, Jan Pedersen, David Ku
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Patent number: 7062504Abstract: A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.Type: GrantFiled: April 25, 2002Date of Patent: June 13, 2006Assignee: The Regents of the University of CaliforniaInventors: Erick Cantu-Paz, Chandrika Kamath
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Patent number: 7007035Abstract: A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.Type: GrantFiled: June 8, 2001Date of Patent: February 28, 2006Assignee: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz
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Publication number: 20050267911Abstract: A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.Type: ApplicationFiled: July 12, 2005Publication date: December 1, 2005Inventors: Chandrika Kamath, Erick Cantu-Paz
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Patent number: 6938049Abstract: A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.Type: GrantFiled: June 11, 2002Date of Patent: August 30, 2005Assignee: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz
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Patent number: 6859804Abstract: A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.Type: GrantFiled: June 11, 2002Date of Patent: February 22, 2005Assignee: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz, David Littau
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Patent number: 6675164Abstract: A data mining system uncovers patterns, associations, anomalies and other statistically significant structures in data. Data files are read and displayed. Objects in the data files are identified. Relevant features for the objects are extracted. Patterns among the objects are recognized based upon the features. Data from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) sky survey was used to search for bent doubles. This test was conducted on data from the Very Large Array in New Mexico which seeks to locate a special type of quasar (radio-emitting stellar object) called bent doubles. The FIRST survey has generated more than 32,000 images of the sky to date. Each image is 7.1 megabytes, yielding more than 100 gigabytes of image data in the entire data set.Type: GrantFiled: June 8, 2001Date of Patent: January 6, 2004Assignee: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz
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Publication number: 20030229641Abstract: A system for decision tree ensembles that includes a module to read the data, a module to create a histogram, a module to evaluate a potential split according to some criterion using the histogram, a module to select a split point randomly in an interval around the best split, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method includes the steps of reading the data; creating a histogram; evaluating a potential split according to some criterion using the histogram, selecting a split point randomly in an interval around the best split, splitting the data, and combining multiple decision trees in ensembles.Type: ApplicationFiled: June 11, 2002Publication date: December 11, 2003Applicant: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz, David Littau
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Publication number: 20030229630Abstract: A system for decision tree ensembles that includes a module to read the data, a module to sort the data, a module to evaluate a potential split of the data according to some criterion using a random sample of the data, a module to split the data, and a module to combine multiple decision trees in ensembles. The decision tree method is based on statistical sampling techniques and includes the steps of reading the data; sorting the data; evaluating a potential split according to some criterion using a random sample of the data, splitting the data, and combining multiple decision trees in ensembles.Type: ApplicationFiled: June 11, 2002Publication date: December 11, 2003Applicant: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz
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Publication number: 20030204508Abstract: A decision tree system that is part of a parallel object-oriented pattern recognition system, which in turn is part of an object oriented data mining system. A decision tree process includes the step of reading the data. If necessary, the data is sorted. A potential split of the data is evaluated according to some criterion. An initial split of the data is determined. The final split of the data is determined using evolutionary algorithms and statistical sampling techniques. The data is split. Multiple decision trees are combined in ensembles.Type: ApplicationFiled: April 25, 2002Publication date: October 30, 2003Applicant: The Regents of the University of CaliforniaInventors: Erick Cantu-Paz, Chandrika Kamath
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Publication number: 20030061228Abstract: A data mining decision tree system that uncovers patterns, associations, anomalies, and other statistically significant structures in data by reading and displaying data files, extracting relevant features for each of the objects, and using a method of recognizing patterns among the objects based upon object features through a decision tree that reads the data, sorts the data if necessary, determines the best manner to split the data into subsets according to some criterion, and splits the data.Type: ApplicationFiled: June 8, 2001Publication date: March 27, 2003Applicant: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz
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Publication number: 20020194159Abstract: A data mining system uncovers patterns, associations, anomalies and other statistically significant structures in data. Data files are read and displayed. Objects in the data files are identified. Relevant features for the objects are extracted. Patterns among the objects are recognized based upon the features. Data from the Faint Images of the Radio Sky at Twenty Centimeters (FIRST) sky survey was used to search for bent doubles. This test was conducted on data from the Very Large Array in New Mexico which seeks to locate a special type of quasar (radio-emitting stellar object) called bent doubles. The FIRST survey has generated more than 32,000 images of the sky to date. Each image is 7.1 megabytes, yielding more than 100 gigabytes of image data in the entire data set.Type: ApplicationFiled: June 8, 2001Publication date: December 19, 2002Applicant: The Regents of the University of CaliforniaInventors: Chandrika Kamath, Erick Cantu-Paz