E-commerce platform individual recommendation method based on weighted frequent item set mining algorithm

A frequent itemset mining and e-commerce platform technology, applied in the field of personalized recommendation for e-commerce platforms, to achieve the effect of improving mining efficiency

Inactive Publication Date: 2018-07-31
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0021] Aiming at the problem of mining weighted frequent itemsets of data sets accessed by users of e-commerce platforms, the present invention provides a personalized recommendation method for e-commerce platforms

Method used

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  • E-commerce platform individual recommendation method based on weighted frequent item set mining algorithm
  • E-commerce platform individual recommendation method based on weighted frequent item set mining algorithm
  • E-commerce platform individual recommendation method based on weighted frequent item set mining algorithm

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specific Embodiment

[0090] By assigning different probability values ​​to the user's click to browse, bookmark, add to the shopping cart and purchase behavior, which are 0.05, 0.3, 0.5 and 1.0 respectively, to reflect the user's preference for different items, thereby constructing the e-commerce platform user access data set D ,like figure 1 shown. In addition, different weight values ​​are assigned to different projects to reflect the benefits that the project brings to merchants. For example, the weight value of project A is 0.05, the weight value of project B is 0.5, the weight value of project C is 0.1, and the weight value of project D is 0.05. 1.0, such as figure 2 shown. Next, with figure 1 The user access data set D of the e-commerce platform and figure 2 Take the weight table shown as an example, set the minimum expected weighted support threshold ε=0.05, describe the steps of the WJDCP-FIM algorithm, and conduct a simple analysis of its performance.

[0091] 1) According to step ...

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Abstract

The invention discloses an e-commerce platform individual recommendation method based on a weighted frequent item set mining algorithm. The method, for the browse behaviors of an e-commerce platform user, assigns different probability values to different items according to behaviors of click browsing, collecting, adding to shopping cart and purchasing so as to reflect the user's preference for different items, and in combination with the income of different items (ie, commodities), mines the weighted frequent item set in an e-commerce platform user browse data set to achieve effective individual recommendation. The invention provides a weight decision downward closure feature and a weighted frequent subset existence characteristic for the e-commerce platform user browse data set weighted frequent item set mining, and provides a uncertain data frequent item set mining algorithm based on weight decision downward closure feature according to the above two characteristics, and takes account of the user's preference for different items and the benefits that the items bring to a merchant, and improves the mining efficiency.

Description

technical field [0001] The invention belongs to the technical field of computer data mining and information processing, and in particular relates to a method for personalized recommendation oriented to an e-commerce platform. Background technique [0002] In recent years, data mining technology has played an increasingly important role in decision support activities in various industries. As one of the most active research fields of data mining, frequent itemset mining refers to the process of discovering frequent patterns in transaction data, and is an important means of discovering association rules in large transaction data sets. It has a wide range of applications in management, medical diagnosis and other fields [1-2]. At present, the theory of frequent pattern mining for deterministic data is becoming more and more mature. However, with the rapid development of information collection technology and data processing technology, various forms of complex data gradually ap...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/06G06F17/30
CPCG06Q30/0631G06F16/2465
Inventor 赵学健孙知信王攀张登银
Owner NANJING UNIV OF POSTS & TELECOMM
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