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A Residue Judgment Method Based on Different Dimensional Features and Comprehensive Evaluation Index

A technology of comprehensive evaluation index and judgment method, which is applied in special data processing applications, market data collection, electronic digital data processing, etc., and can solve problems such as not taking into account the degree of commodity screening conditions and not being scientific

Inactive Publication Date: 2017-08-01
SICHUAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Such a processing method is not scientific because it does not take into account the degree to which the product meets and does not meet the various screening conditions.

Method used

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  • A Residue Judgment Method Based on Different Dimensional Features and Comprehensive Evaluation Index
  • A Residue Judgment Method Based on Different Dimensional Features and Comprehensive Evaluation Index
  • A Residue Judgment Method Based on Different Dimensional Features and Comprehensive Evaluation Index

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Embodiment Construction

[0036] The present invention will be further described below in conjunction with embodiment:

[0037] First, define product satisfaction and dissatisfaction in each dimension. Assume that a product data set containing n data dimensions (performance indicators) of m products can be expressed as a matrix D m×n , defined as follows,

[0038] D. m×n ={d i =(d i,0 , d i,1 ,...,d i,j ,...,d i,n-1 ) T |0≤i≤m-1,0≤j≤n-1} (1)

[0039] set pos j 、neg j Respectively represent the satisfaction and dissatisfaction of the product on the j dimension, and respectively represent the degree of satisfaction or dissatisfaction of the product on the j dimension that satisfies the screening conditions or does not meet the screening conditions. The value ranges are as follows,

[0040]

[0041] That is, when a product satisfies the filter conditions in a certain dimension, its dissatisfaction in this dimension is 0, and the value range of its satisfaction is [0,1]; otherwise, if the pro...

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Abstract

A residue decision algorithm based on different dimensionality features and comprehensive evaluation index includes the steps of calculating satisfaction degrees and dissatisfaction degrees of unscreened commodities based on different dimensionality features; calculating overall satisfaction degree and dissatisfaction degree of the unscreened commodities; calculating a comprehensive evaluation index of the commodities; and judging residue. The algorithm has the advantages that the commodities can be completed more reasonably and effectively, and the commodities, which are unsatisfactory to but close to part of screening conditions, which are highly satisfactory to other screening conditions and which are highly possible to be popular with users, are reserved for the users more representatively and more scientifically.

Description

technical field [0001] The invention relates to the technical field of product selection in e-commerce website shopping, and specifically relates to a residue determination algorithm based on different dimension features and comprehensive evaluation indexes. Background technique [0002] Commodity screening refers to screening and comparative selection of commodities (especially commodities under the same category) according to conditions. The quality of user experience in this process is one of the most important indicators for users to evaluate the shopping experience of various e-commerce websites. [0003] Due to the user's uncertainty about the filter conditions, there may be errors between the filter results and user needs. For example, when users filter products, it often happens that some products do not meet some of the filter conditions while highly meeting other filter conditions; such products will be filtered out in the screening system, but they are often accep...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06Q30/02
CPCG06F16/9535G06Q30/0201
Inventor 朱敏李明召甘启宏梁婷李一
Owner SICHUAN UNIV
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