Processing of categorized product information
First Claim
1. A data processing system, comprising:
- one or more processors configured to;
access a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein;
a leaf category level of the plurality of hierarchical levels comprises a leaf category node;
the leaf category node includes product information;
the product information comprises a plurality of product attribute parameters;
the plurality of product attribute parameters comprises non-standard product information and standard product information; and
the standard product information comprises a plurality of non-product attribute parameters;
select, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information;
partition standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information, and wherein the representative product attribute parameter comprises a price of the product, a material of the product, a brand of the product, a model number of the product, a weight of the product, or any combination thereof;
determine whether values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet an established criterion; and
in the event that the values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet the established criterion;
determine a degree of similarity of non-product attribute parameters within each subset;
determine whether the degree of similarity of non-product attribute parameters within each subset meets a threshold value; and
in the event that the degree of similarity of non-product attribute parameters within anyone subset fails to meet the threshold value;
determine one of the product attribute parameters having a value that meets the established criterion;
determine a set to which the one product attribute parameter belongs; and
partition the non-standard product information into a subset of the determined set to which the one product attribute parameter belongs based on the non-product attribute parameters of the non-standard product information; and
one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions.
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Abstract
Data processing includes accessing a product category tree, the product category tree comprising a plurality of hierarchical levels. A leaf category level of the plurality of hierarchical levels comprises a leaf category node. The leaf category node includes product information. The product information comprises a plurality of product attribute parameters. The plurality of product attribute parameters comprises standard product information. Data processing further includes selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; and partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information.
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Citations
14 Claims
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1. A data processing system, comprising:
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one or more processors configured to; access a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein; a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters; the plurality of product attribute parameters comprises non-standard product information and standard product information; and the standard product information comprises a plurality of non-product attribute parameters; select, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partition standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information, and wherein the representative product attribute parameter comprises a price of the product, a material of the product, a brand of the product, a model number of the product, a weight of the product, or any combination thereof; determine whether values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet an established criterion; and in the event that the values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet the established criterion; determine a degree of similarity of non-product attribute parameters within each subset; determine whether the degree of similarity of non-product attribute parameters within each subset meets a threshold value; and in the event that the degree of similarity of non-product attribute parameters within anyone subset fails to meet the threshold value; determine one of the product attribute parameters having a value that meets the established criterion; determine a set to which the one product attribute parameter belongs; and partition the non-standard product information into a subset of the determined set to which the one product attribute parameter belongs based on the non-product attribute parameters of the non-standard product information; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A data processing method, comprising:
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accessing a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein; a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters; the plurality of product attribute parameters comprises non-standard product information and standard product information; and the standard product information comprises a plurality of non-product attribute parameters; selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information, and wherein the representative product attribute parameter comprises a price of the product, a material of the product, a brand of the product, a model number of the product, a weight of the product, or any combination thereof; determining whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning fail to meet an established criterion; and in the event that the values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet the established criterion; determining a degree of similarity of non-product attribute parameters within each subset; determining whether the degree of similarity of non-product attribute parameters within each subset meets a threshold value; and in the event that the degree of similarity of non-product attribute parameters within anyone subset fails to meet the threshold value; determining one of the product attribute parameters having a value that meets the established criterion; determining a set to which the one product attribute parameter belongs; and partitioning the non-standard product information into a subset of the determined set to which the one product attribute parameter belongs based on the non-product attribute parameters of the non-standard product information.
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14. A computer program product for data processing, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for:
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accessing a product category tree, the product category tree comprising a plurality of hierarchical levels, wherein; a leaf category level of the plurality of hierarchical levels comprises a leaf category node; the leaf category node includes product information; the product information comprises a plurality of product attribute parameters; the plurality of product attribute parameters comprises non-standard product information and standard product information; and the standard product information comprises a plurality of non-product attribute parameters; selecting, among the plurality of product attribute parameters that correspond to the leaf category node, a representative product attribute parameter that is representative of the product information; partitioning standard product information of the leaf category node to obtain a plurality of sets using the representative product attribute parameter, wherein each of the plurality of sets includes at least some of the standard product information, and wherein the representative product attribute parameter comprises a price of the product, a material of the product, a brand of the product, a model number of the product, a weight of the product, or any combination thereof; determining whether values of product attribute parameters that correspond to the non-standard product information and used for set partitioning fail to meet an established criterion; and in the event that the values of product attribute parameters in the non-standard product information and used for set partitioning fail to meet the established criterion; determining a degree of similarity of non-product attribute parameters within each subset; determining whether the degree of similarity of non-product attribute parameters within each subset meets a threshold value; and in the event that the degree of similarity of non-product attribute parameters within anyone subset fails to meet the threshold value; determining one of the product attribute parameters having a value that meets the established criterion; determining a set to which the one product attribute parameter belongs; and partitioning the non-standard product information into a subset of the determined set to which the one product attribute parameter belongs based on the non-product attribute parameters of the non-standard product information.
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Specification