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.
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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.
155 Citations
43 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. - 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, 25)
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26. 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. - View Dependent Claims (27, 28)
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29. 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 (30, 31, 32, 33)
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34. A method for use in targeting assets in a broadcast network, comprising the steps of:
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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. - View Dependent Claims (35, 36, 37)
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38. 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; and
signaling said broadcast network based on the user information. - View Dependent Claims (39, 40)
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41. 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; and
an interface, operatively associated with the processor, for use in signaling said broadcast network based on the user information. - View Dependent Claims (42, 43)
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Specification