Goods recommending method and system

A recommendation method and recommendation system technology, applied in the field of big data, can solve problems such as poor practicability, and achieve the effect of strong practicability and strong pertinence

Inactive Publication Date: 2018-06-01
北京思特奇信息技术股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In shopping malls, channel portals, and most commodity trading applications, hot-selling or emerging commodities are usually recommended to visiting users through advertising spaces or recommendation columns. However, the current recommen

Method used

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  • Goods recommending method and system
  • Goods recommending method and system
  • Goods recommending method and system

Examples

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Example Embodiment

[0049] The principles and features of the present invention will be described below with reference to the accompanying drawings. The examples cited are only used to explain the present invention and are not used to limit the scope of the present invention.

[0050] Such as figure 1 Shown is a schematic flow chart provided by an embodiment of a method for recommending a commodity according to the present invention, and the method includes:

[0051] S1: Obtain user behavior logs generated when users purchase or browse commodities.

[0052] It should be noted that the user behavior log refers to a collection of user purchase or browsing behavior data generated by the background system when the user purchases or browses the product.

[0053] For example, the user behavior log may be: xx time, xx users, purchase (or browse) xx products through the xx platform.

[0054] It should be noted that user behavior logs can be collected through intrusive or non-intrusive code insertion on the front-e...

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PUM

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Abstract

The invention discloses a goods recommending method and system, and relates to the big data field; the method comprises the following steps: obtaining a user behavior log formed by the user buying orbrowsing goods; processing the user behavior log so as to obtain feature information of the user buying or browsing goods; weighting the feature information according to a preset weight coefficient, thus obtaining a goods recommending level; recommending the goods according to the recommending level. The method and system obtain the user behavior log formed by the user buying or browsing goods, extract the feature information of the user buying or browsing goods, obtain the goods recommending level according to the feature information, and recommend the goods according to the level, thus satisfying advertisement input demands of different users, and providing customized advertisement recommendations for various users; the method and system are strong in pertinency and practical values.

Description

technical field [0001] The present invention relates to the field of big data, in particular to a product recommendation method and system. Background technique [0002] In shopping malls, channel portals, and most commodity trading applications, hot-selling or emerging commodities are usually recommended to visiting users through advertising spaces or recommendation columns. However, the current recommendation effect can only be fixed regardless of the needs of users. The recommendation of one or several products with large sales or new products, or the products that users have browsed and purchased has the disadvantage of poor practicability. Contents of the invention [0003] The technical problem to be solved by the present invention is to provide a product recommendation method and system for the deficiencies of the prior art. [0004] The technical scheme that the present invention solves the problems of the technologies described above is as follows: [0005] A me...

Claims

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Application Information

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IPC IPC(8): G06Q30/06
CPCG06Q30/0631
Inventor 杨凯
Owner 北京思特奇信息技术股份有限公司
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