Retail recommendation domain model
First Claim
1. A computer-based method of generating recommendations for potential purchase by a customer, comprising:
- transforming a part catalog into a normalized part catalog by mapping at least one generic catalog item from the part catalog into a set of normalized catalog items based on attribute names and values corresponding to the generic catalog item;
transforming a transaction history data set into a normalized transaction history data set with a computer system by mapping at least one generic item from the transaction history data set into a set of normalized items based on attribute names and values corresponding to the generic item;
generating association rules based on the normalized transaction history data set;
transforming a recommendation context into a normalized transaction data set by mapping at least one customer item from the recommendation context into a set of normalized transaction items based on attribute names and values corresponding to the customer item;
generating a recommendation by selecting a rule from the association rules that best matches with the normalized transaction data set.
3 Assignments
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Accused Products
Abstract
A data processing system normalizes data sets (such as low-resolution transaction data) into high-resolution data sets by mapping generic information into attribute-based specific information that is stored in a database. By establishing a shared domain model for representing items in the recommendation context, catalog and quote history with common terms and concepts, a recommendation engine operating in the shared domain may process the attribute-based representations to make specific and relevant recommendations to the customer. In addition, when certain attribute values are normalized over time, recommendations derived from past order history can be intelligently applied to current orders. The normalized representation of elements in the shared domain may also be used to generate compelling selling point text for each recommendation that is specific to the marketing objectives of the seller and identifies the objectives of the buyer.
96 Citations
20 Claims
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1. A computer-based method of generating recommendations for potential purchase by a customer, comprising:
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transforming a part catalog into a normalized part catalog by mapping at least one generic catalog item from the part catalog into a set of normalized catalog items based on attribute names and values corresponding to the generic catalog item; transforming a transaction history data set into a normalized transaction history data set with a computer system by mapping at least one generic item from the transaction history data set into a set of normalized items based on attribute names and values corresponding to the generic item; generating association rules based on the normalized transaction history data set; transforming a recommendation context into a normalized transaction data set by mapping at least one customer item from the recommendation context into a set of normalized transaction items based on attribute names and values corresponding to the customer item; generating a recommendation by selecting a rule from the association rules that best matches with the normalized transaction data set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A system for generating purchase recommendations for a customer, comprising:
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a database for storing a transaction history data set; means for transforming the transaction history data set into an attribute-based transaction history data set; means for generating association rules from the attribute-based transaction history data set; means for transforming a recommendation context generated by a customer into an attribute-based transaction data set; and a recommendation engine for generating a recommendation by selecting a rule from the association rules that best matches with the attribute-based transaction data set.
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Specification