Other

Garbortese Holdings, LLC

Thinkalike, LLC

Ivan Pope

Alan Sullivan

Alan T Sullivan

A system and method for controlling information output based on user feedback about the information is provided. At least one neural network module selects one or more of a plurality of objects to receive information from a plurality of information sources based at least in part on a plurality of inputs and a plurality of weight values during an epoch. The information sources may include electronic mail providers, chat participants, or page links. Recipients of the objects provide feedback about the information during an epoch. At the conclusion of an epoch, the neural network takes the feedback and generates a rating value for each of the plurality of objects. Based on the rating value and the selections made, the neural network redetermines the weight values within the network. The neural network then selects the objects to receive information during a subsequent epoch using the redetermined weight values and the inputs for that subsequent epoch.

Neural network system and method for controlling information output based on user feedback

A system and method for controlling information output based on user feedback about the information is provided that comprises a plurality of information sources providing information. The information sources may be electronic mail providers, chat participants, or page links. At least one neural network module selects one or more of a plurality of objects to receive information from the plurality of information sources based at least in part on a plurality of inputs and a plurality of weight values during that epoch. At least one server, associated with the neural network module, provides one or more of the objects to a plurality of recipients. The objects may comprise electronic mail messages, chat participants viewers, or slots within a link directory page. The recipients provide feedback about the information during an epoch. At the conclusion of an epoch, the neural network takes all of the feedback that has been provided from the recipients and generates a rating value for each of the plurality of objects. Based on the rating value and the selections made, the neural network redetermines the weight values within the network. The neural network then selects the objects to receive information during a subsequent epoch using the redetermined weight values and the inputs for that subsequent epoch.

A system and method for controlling information output based on user feedback about the information that includes a plurality of information sources. At least one neural network module selects one or more of a plurality of objects to receive information from the plurality of information sources based on a plurality of inputs and a plurality of weight values during that epoch. At least one server, associated with the neural network module, provides one or more of the objects to a plurality of recipients. The recipients provide feedback during an epoch. At the conclusion of an epoch, the neural network takes the feedback that has been provided from the recipients and generates a rating value for each of the objects. Based on the rating value and selections made, the neural network redetermines the weight values. The neural network then selects the objects to receive information during a subsequent epoch.

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London, United Kingdom

Ivan Pope