Commodity recommendation system based on decision-making efficient negative sequence rule mining and working method thereof

A product recommendation, negative sequence technology, applied in business, data processing applications, special data processing applications, etc., can solve problems such as non-conformity with customer needs, contradictions, information redundancy, etc., to reduce data loss rate, reduce expenses, Effective effect of security and quality of service

Active Publication Date: 2020-11-17
山东元竞信息科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, one of the shortcomings is that sometimes the recommended products provided to users obviously do not meet the needs of customers
Although the existing product recommendation methods can obtain a lot of information, a large part of the information is redundant or even contradictory. How to filter ou...

Method used

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  • Commodity recommendation system based on decision-making efficient negative sequence rule mining and working method thereof
  • Commodity recommendation system based on decision-making efficient negative sequence rule mining and working method thereof
  • Commodity recommendation system based on decision-making efficient negative sequence rule mining and working method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0071] A product recommendation system based on decision-making high-utility negative sequence rule mining, such as figure 1 As shown in , it includes an information collection module, a product recommendation module, and a product sales module that are sequentially connected through transmission network communication;

[0072] The information collection module includes an information extraction module and a first information transmission module connected in sequence; the information extraction module is used to: extract and save customer behavior data in real time, and the customer behavior data includes customer ID, face mark, gender, age, time stamp , the logo of the commodity browsed by the customer; the first information transmission module is used to: transmit the behavior data of the customer to the commodity recommendation module through the transmission network;

[0073] The commodity recommendation module includes an information processing module, an information anal...

Embodiment 2

[0078] The working method of the product recommendation system based on the decision-making high-utility negative sequence rule mining described in embodiment 1 includes the following steps:

[0079] (1) The information extraction module extracts and saves the customer's behavior data in real time. The customer's behavior data includes customer ID, face mark, gender, age, time stamp, and the product mark that the customer browses; among them, face marks such as whether to wear glasses, Eye coordinates.

[0080] (2) The first information transmission module transmits the customer's behavior data extracted by the step (1) information collection module to the product recommendation module through the transmission network;

[0081] (3) The information processing module performs data cleaning on the collected customer behavior data, and performs data classification on the data after data cleaning;

[0082] (4) According to the processing results of the information processing modul...

Embodiment 3

[0087] According to the working method of the product recommendation system based on the decision-making high-utility negative sequence rule mining described in embodiment 2, the steps are as follows:

[0088] In this embodiment, the shopping data records of snacks sold in an offline store of a shopping mall are used as experimental data. Table 1 and Table 2 are the partial results of preprocessing customer shopping behavior data into utility sequence database and utility table respectively.

[0089] Table 1

[0090] Customer ID shopping sequence C1

C2

C3

… …

[0091] Table 2

[0092] item Walnut Pecans dried strawberries Spicy Dried Tofu dried mango Unit utility (yuan / 1kg) 166.9 146 150 113 216

[0093] step (3), because real-world data are generally incomplete, noisy and inconsistent. When collecting customer behavior data through the information collection module, there may be missing values, ...

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Abstract

The invention relates to a commodity recommendation system based on decision-making efficient negative sequence rule mining and a working method of the commodity recommendation system. The commodity recommendation system comprises an information acquisition module, a commodity recommendation module and a commodity sales module which are connected in sequence, extracting and storing behavior data of customers in real time, and transmitting the behavior data to a commodity recommendation module; performing data cleaning and data classification on the acquired behavior data of the customer; analyzing and predicting the shopping behavior of the customer; establishing a shopping behavior sequence corresponding to the customer ID, wherein the shopping behavior data of the customers with the samegender and the same age interval form a sequence database; mining the sequence database to obtain a decidable high-efficiency negative sequence rule meeting the requirements, namely, commodity recommendation meeting the requirements of the customer; according to the method, the statistical correlation between the things is considered, the semantic meaning between the things is also considered, many useless rules can be deleted, and more meaningful rules which can be directly used for decision making are obtained.

Description

technical field [0001] The invention relates to a product recommendation system and a working method based on mining of decision-making high-utility negative sequence rules, and belongs to the application technical field of decision-making high-utility negative sequence rules. Background technique [0002] The popularization of Internet technology has promoted the rapid development of online e-commerce. The advantage of online e-commerce is that it can identify different users based on user accounts, browser cookies, etc., and then recommend products to users based on their historical browsing and purchase records. However, one of the shortcomings is that sometimes the recommended products provided to users obviously do not meet the needs of customers. In addition, offline stores are still an important way to sell goods, but due to their lack of intelligence, it is impossible to achieve product recommendations and corresponding user experience similar to online e-commerce. ...

Claims

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Application Information

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IPC IPC(8): G06F16/2458G06F16/9535G06K9/62G06Q30/06
CPCG06F16/2465G06F16/9535G06Q30/0631G06F18/24G06Q30/0282
Inventor 董祥军张孟姣
Owner 山东元竞信息科技有限公司
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