Patents by Inventor Anna L. Buczak

Anna L. Buczak 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).

  • Patent number: 6957200
    Abstract: Sensors are selected from a sensor network for tracking of at least one target. The sensors are selected using a genetic algorithm construct having n chromosomes, wherein each chromosome represents one sensor, defining a fitness function based on desired attributes of the tracking, selecting one or more of the individuals for inclusion in an initial population, executing a genetic algorithm on the initial population until defined convergence criteria are met, wherein execution of the genetic algorithm has the steps of choosing the fittest individual from the population, choosing random individuals from the population and creating offspring from the fittest and randomly chosen individuals. In one embodiment, only i chromosomes are mutated during any one mutation, wherein i has a value of from 2 to n?1.
    Type: Grant
    Filed: June 27, 2001
    Date of Patent: October 18, 2005
    Assignee: Honeywell International, Inc.
    Inventors: Anna L. Buczak, Henry Wang
  • Patent number: 6922680
    Abstract: A method and apparatus are disclosed for recommending items of interest by fusing a plurality of recommendation scores from individual recommendation tools using one or more Radial Basis Function neural networks. The Radial Basis Function neural networks include N inputs and at least one output, interconnected by a plurality of hidden units in a hidden layer. A unique neural network can be used for each user, or a neural network can be shared by a plurality of users, such as a set of users having similar characteristics. A neural network training process initially trains each Radial Basis Function neural network using data from a training data set. A neural network cross-validation process selects the Radial Basis Function neural network that performs best on the cross-validation data set. A neural network program recommendation process uses the selected neural network(s) to recommend items of interest to a user.
    Type: Grant
    Filed: March 19, 2002
    Date of Patent: July 26, 2005
    Assignee: Koninklijke Philips Electronics N.V.
    Inventor: Anna L. Buczak
  • Publication number: 20040093282
    Abstract: A method for providing previous selection information to a user is provided that includes generating a list of possible selections based on a selection request received from the user. A selection history table is accessed to identify previous selections by the user. A determination is made regarding whether a selection in the list of possible selections matches a previous selection. The user is informed when a determination is made that a selection in the list of possible selections matches a previous selection.
    Type: Application
    Filed: November 8, 2002
    Publication date: May 13, 2004
    Applicant: KONINKLIJKE PHILIPS ELECTRONICS N.V.
    Inventors: Anna L. Buczak, John Zimmerman, Kaushal Kurapati
  • Publication number: 20030229896
    Abstract: A method of fusing recommender scores includes the steps of: (a) providing a first recommender score for a topic of interest based on a first set of information; (b) providing a second recommender score for the topic of interest based on a second set of information; (c) fusing the first recommender score and the second recommender score by compensatory fuzzy aggregation connectives; and (d) providing a final recommendation for the topic of interest based on the fusion in step (c). The method may include providing at least a third recommender score, and step (c) includes fusing the third recommender score with the first recommender score and the second recommender score. The final recommendation can be output on one of a display unit and a television set. The compensatory fuzzy aggregation connectives used for fusing in step (c) may include a Generalized Mean or a Gamma Model.
    Type: Application
    Filed: June 10, 2002
    Publication date: December 11, 2003
    Applicant: Koninklijke Philips Electronics N.V.
    Inventor: Anna L. Buczak
  • Publication number: 20030182249
    Abstract: A method and apparatus are disclosed for recommending items of interest by fusing a plurality of recommendation scores from individual recommendation tools using one or more Radial Basis Function neural networks. The Radial Basis Function neural networks include N inputs and at least one output, interconnected by a plurality of hidden units in a hidden layer. A unique neural network can be used for each user, or a neural network can be shared by a plurality of users, such as a set of users having similar characteristics. A neural network training process initially trains each Radial Basis Function neural network using data from a training data set. A neural network cross-validation process selects the Radial Basis Function neural network that performs best on the cross-validation data set. A neural network program recommendation process uses the selected neural network(s) to recommend items of interest to a user.
    Type: Application
    Filed: March 19, 2002
    Publication date: September 25, 2003
    Applicant: Koninklijke Philips Electronics N.V.
    Inventor: Anna L. Buczak
  • Publication number: 20030126606
    Abstract: A method and system for providing hierarchical decision fusion of recommender scores, wherein at least two levels of fusion are provided. In a method, a plurality of recommenders at a first level are grouped according to topics of interest. A plurality of first level fusion centers receive a number of outputs from a predetermined number of recommenders. The first level fusion centers output a first enhanced decision level, and a series of second level fusion centers receive a predetermined number of the first enhanced decision, and a second fusing step occurs to result in a second enhanced decision level. The groups can be reading history, music, viewing history, purchasing history, and can be intermixed, so that the enhanced decision may recommend a particular movie based on both the ranking about movies and music.
    Type: Application
    Filed: December 27, 2001
    Publication date: July 3, 2003
    Applicant: Koninklijke Philips Esectronics N.V.
    Inventors: Anna L. Buczak, J. David Schaffer
  • Publication number: 20030050902
    Abstract: The invention includes a method for selecting sensors from a sensor network for tracking of at least one target having the steps of defining an individual of a genetic algorithm construct having n chromosomes, wherein each chromosome represents one sensor, defining a fitness function based on desired attributes of the tracking, selecting one or more of the individuals for inclusion in an initial population, executing a genetic algorithm on the initial population until defined convergence criteria are met, wherein execution of the genetic algorithm has the steps of choosing the fittest individual from the population, choosing random individuals from the population and creating offspring from the fittest and randomly chosen individuals.
    Type: Application
    Filed: June 27, 2001
    Publication date: March 13, 2003
    Inventors: Anna L. Buczak, Henry (Hui) Wang