Fuzzy logic based viewer identification for targeted asset delivery system
First Claim
1. A method for use in targeting assets in a broadcast network, comprising the steps of:
- identifying an asset having a target audience defined by one or more targeting parameters;
first using a machine learning tool to develop classification information for one or more users of a user equipment device audience; and
second using the machine learning tool to match said identified asset to a current user of said user equipment device;
wherein said step of second using comprises using fuzzy logic to determine a level of correspondence between user classification parameters of said user and said targeting parameters of said asset.
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Accused Products
Abstract
A targeted advertising system uses a machine learning tool to select an asset for a current user of a user equipment device, for example, to select an ad for delivery to a current user of a digital set top box in a cable network. The machine learning tool first operates in a learning mode to receive user inputs and develop evidence that can characterize multiple users of the user equipment device audience. In a working mode, the machine learning tool processes current user inputs to match a current user to one of the identified users of that user equipment device audience. Fuzzy logic may be used to improve development of the user characterizations, as well as matching of the current user to those developed characterizations. In this manner, targeting of assets can be implemented not only based on characteristics of a household but based on a current user within that household.
252 Citations
38 Claims
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1. A method for use in targeting assets in a broadcast network, comprising the steps of:
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identifying an asset having a target audience defined by one or more targeting parameters; first using a machine learning tool to develop classification information for one or more users of a user equipment device audience; and second using the machine learning tool to match said identified asset to a current user of said user equipment device;
wherein said step of second using comprises using fuzzy logic to determine a level of correspondence between user classification parameters of said user and said targeting parameters of said asset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A method for use in targeting assets in a broadcast network, comprising the steps of:
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receiving user inputs at a user equipment device; and analyzing the inputs to associate audience classification parameters with a user using fuzzy logic, wherein said fuzzy logic involves one of fuzzy sets and fuzzy rules;
wherein said step of analyzing comprises identifying a user input, associating the input with a classification parameter of a current user and treating said input as a point in a frizzy set. - View Dependent Claims (26)
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27. An apparatus for use in targeting assets in a broadcast network, comprising:
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an interface for receiving user inputs at a user equipment device; and a processor for analyzing the inputs to associate audience classification parameters with the user using a machine learning tool, wherein the machine learning tool is operative to develop classification information for a plurality of users of a user equipment device audience and to identify a current user of said user equipment device. - View Dependent Claims (28, 29, 30, 31)
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32. A method for use in targeting assets in a broadcast network, comprising the steps of
developing a model of a network user based on user inputs free from persistent storage of a profile of said user; - and
using the model of the network user in targeting assets to the user;
wherein said step of developing comprises operating a machine learning tool to receive inputs from a plurality of users over time, associating said inputs with user classification information to develop evidence and processing said evidence to provide said model of said network user;
wherein said machine learning tool progressively develops the model after each user input. - View Dependent Claims (33, 34)
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35. A method for use in targeting assets in a broadcast network, comprising the steps of:
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determining, at a user equipment device, user information regarding a user of said user equipment device based at least in part on user inputs to said user equipment device using a machine learning tool; and signaling said broadcast network based on the user information;
wherein said step of signaling comprises providing an indication to the network regarding a suitability of an asset for said user. - View Dependent Claims (36)
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37. An apparatus for use in targeting assets in a broadcast network, comprising:
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a processor associated with a user equipment device operative for determining information regarding a user of said user equipment device based at least in part on user inputs to said user equipment device using a machine learning tool; and an interface, operatively associated with the processor, for use in signaling said broadcast network based on the user information;
wherein said interface is used to provide information to the network regarding an asset delivered at said user equipment device. - View Dependent Claims (38)
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Specification