Commodity recommendation method based on multidimensional user consumption propensity modeling

A product recommendation and multi-dimensional technology, applied in marketing and other directions, can solve problems such as blind recommendation and less consideration of user consumption tendency

Inactive Publication Date: 2013-09-25
姚明东
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The existing recommendation methods seldom consider the user’s consumption tendency, so they are more blind when recommending. In fact, the purpose of customers is relatively clear when they consume. Low-end products often form invalid recommendations

Method used

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  • Commodity recommendation method based on multidimensional user consumption propensity modeling
  • Commodity recommendation method based on multidimensional user consumption propensity modeling
  • Commodity recommendation method based on multidimensional user consumption propensity modeling

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Experimental program
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Embodiment Construction

[0016] The present invention will be described in detail below in conjunction with specific embodiments.

[0017] 1. According to the user's browsing and purchase records recorded by the e-commerce system, obtain the categories that the user is interested in

[0018] 2. Under each category, establish a multi-dimensional tendency vector model to determine the dimensions of judgment, such as:

[0019] 1) Price: the price level of the product purchased by the user, for example, the price dimension = (high, medium, low)

[0020] 2) Discount: user's tendency towards discounted products, such as discount dimension = (sensitive, insensitive)

[0021] 3) Brand: the tendency of users to choose product brands, such as brand dimension = (domestic, Japanese, Korean, European and American)

[0022] 4) Seller: the user's tendency to choose a product seller, such as seller dimension = (platform self-operated, third-party operation)

[0023] 5) Periodic consumption: user's periodic consump...

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Abstract

The invention discloses a commodity recommendation method based on multidimensional user consumption propensity modeling. According to the method, through analyzing multidimensional information such as a user browsing history, a consumption record and a user behavior record, the real consumption propensity of the user is speculated, and the method has a very important actual application value for the improvement of a personalized commodity recommendation effect and the conversion of the effect into an actual purchase behavior. Firstly, a multidimensional user consumption propensity model for the field of electronic commerce can be obtained, and a foundation is laid for the following personalized recommendation. Secondly, combined with a user interest classification and a cyclical consumption dimension propensity analysis, a personalized commodity recommendation effect in accordance with the consumption propensity of a client can be provided to the client. The method result can be widely applied to an electronic commerce recommendation application system.

Description

technical field [0001] The invention relates to the field of e-commerce, in particular to a product recommendation method based on multi-dimensional user consumption tendency modeling. Targeted product recommendations are made by analyzing user consumption tendencies to improve recommendation accuracy and conversion rate. Background technique [0002] The existing recommendation methods seldom consider the user’s consumption tendency, so they are more blind when recommending. In fact, the purpose of customers is relatively clear when they consume. Low-end products often form invalid recommendations. [0003] Therefore, there are defects in the prior art and need to be improved. Contents of the invention [0004] Aiming at the characteristics of the e-commerce field, the present invention proposes a product recommendation method based on multi-dimensional user consumption tendency modeling. One is to obtain a multi-dimensional user consumption propensity model for e-comm...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
Inventor 姚明东范英磊陈浩
Owner 姚明东
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