CONSUMER DECISION TREE GENERATION SYSTEM
First Claim
1. A computer readable medium having instructions stored thereon that, when executed by a processor, causes the processor to generate a consumer decision tree (CDT) comprising a plurality of nodes, the generate the consumer decision tree comprising:
- receiving customer purchasing data comprising transactions of a plurality of products each having at least one product attribute;
for a product category, identifying a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product;
assigning the product category as a current level of the CDT;
determining a most significant attribute of the plurality of attributes for the current level;
forming a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, wherein each sub-section corresponds to an attribute value of the most significant attribute; and
assigning each of the sub-sections as the current level and repeating the determining the most significant attribute and forming the next level of the CDT for each sub-section until a terminal node is identified.
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Accused Products
Abstract
A system generates a consumer decision tree (“CDT”). The system receives customer purchasing data that includes transactions of a plurality of products each having at least one product attribute. For a product category, the system identifies a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product. The system assigns the product category as a current level of the CDT, and determines a most significant attribute of the plurality of attributes for the current level. The system forms a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, where each sub-section corresponds to an attribute value of the most significant attribute. The system then forms a next level of the CDT for each sub-section until a terminal node is identified.
32 Citations
20 Claims
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1. A computer readable medium having instructions stored thereon that, when executed by a processor, causes the processor to generate a consumer decision tree (CDT) comprising a plurality of nodes, the generate the consumer decision tree comprising:
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receiving customer purchasing data comprising transactions of a plurality of products each having at least one product attribute; for a product category, identifying a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product; assigning the product category as a current level of the CDT; determining a most significant attribute of the plurality of attributes for the current level; forming a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, wherein each sub-section corresponds to an attribute value of the most significant attribute; and assigning each of the sub-sections as the current level and repeating the determining the most significant attribute and forming the next level of the CDT for each sub-section until a terminal node is identified. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer implemented method for generating a consumer decision tree (CDT) comprising a plurality of nodes, the method comprising:
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receiving customer purchasing data comprising transactions of a plurality of products each having at least one product attribute; for a product category, identifying a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product; assigning the product category as a current level of the CDT; determining a most significant attribute of the plurality of attributes for the current level; forming a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, wherein each sub-section corresponds to an attribute value of the most significant attribute; and assigning each of the sub-sections as the current level and repeating the determining the most significant attribute and forming the next level of the CDT for each sub-section until a terminal node is identified. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A consumer decision tree (CDT) generation system comprising:
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a processor; a memory coupled to the processor and storing instructions that cause the processor to; receive customer purchasing data comprising transactions of a plurality of products each having at least one product attribute; for a product category, identify a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product; assign the product category as a current level of the CDT; determine a most significant attribute of the plurality of attributes for the current level; form a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, wherein each sub-section corresponds to an attribute value of the most significant attribute; and assign each of the sub-sections as the current level and repeating the determine the most significant attribute and form the next level of the CDT for each sub-section until a terminal node is identified. - View Dependent Claims (17, 18, 19, 20)
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Specification