Effective dynamic commodity recommendation method and commodity recommendation system

A product recommendation and product technology, applied in marketing and other directions to achieve strong dynamic effects

Active Publication Date: 2012-08-08
ZHEJIANG UNIV
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

But it’s hard to imagine that when a user buys an iPhone and recommends an iPad, the user will immedia

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  • Effective dynamic commodity recommendation method and commodity recommendation system
  • Effective dynamic commodity recommendation method and commodity recommendation system
  • Effective dynamic commodity recommendation method and commodity recommendation system

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0034] Before introducing the specific steps of the method, several relevant definitions are given.

[0035] Definition 1. Support: The quantitative connection value between two commodities, which is the frequency of common occurrence of commodities. The specific calculation method is described in detail below. This defines the minimum support threshold, which represents the minimum support between two connected items.

[0036] Definition 2. Frequent commodity pairs: If the support between two commodities exceeds the minimum support threshold, the two commodities are called frequent commodity pairs; in a commodity set, if any two commodities are frequent commodity pairs, then This set is called a frequent item set. Frequent item pairs are actually frequent binomial item sets.

[0037] Definition 3. Associated purchase relationship of frequen...

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Abstract

The invention discloses a commodity recommendation system and a commodity recommendation method. The system comprises a purchase record source module, a control device module, a filter module, a commodity pair frequency calculation device module and a frequent set database module. Each module is connected according to a network connection mode. The purchase record source module records information when a user purchases a commodity through a purchase record table. The control device module is used for providing an interface of each module and controlling access of data, issue of interruption and setting of a threshold, and can operate other modules. The filter module receives a set threshold from the control device module and carries out direct filtration on data which does not reach the threshold. The commodity pair frequency calculation device module is used for executing a calculation process in the method. The frequent set database module stores a final frequent database, and updates a source database in the purchase record source module. According to the method and the system, a common frequency set excavation scheme is utilized, a time factor is added, and dynamic performance is extremely strong when recommending the commodity.

Description

technical field [0001] The invention belongs to the field of electronic commerce, and mainly uses database information retrieval technology and data mining technology to recommend interested commodities to customers. Background technique [0002] With the development of network technology in the information age and the continuous improvement of online trading platforms, online shopping has gradually become a living habit of people. Various e-commerce sites are targeting this market, and the competition for customers is fierce. How to improve user stickiness is an important issue for e-commerce websites to consider. In addition to offline related product quality, express delivery speed, etc., there are also many ways to attract customers online. Personalized recommendations for users will not only make users more interested, but also increase the order volume of the website to a certain extent, tap potential customers, and increase the final revenue. Therefore, various per...

Claims

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Application Information

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IPC IPC(8): G06Q30/02
Inventor 吴健马莹潘李敏陈亮
Owner ZHEJIANG UNIV
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