Commodity information recommending method and commodity information recommending system based on user historical behaviors

A product information and product recommendation technology, applied in the field of product information recommendation, can solve the problem of not being able to predict unpurchased products or the purchase probability of a single product, and achieve the effect of accurate recommendation

Active Publication Date: 2017-03-08
深圳市云网万店科技有限公司 +1
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Problems solved by technology

These methods are all aimed at predicting the purchase probability of users or users for cat

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  • Commodity information recommending method and commodity information recommending system based on user historical behaviors
  • Commodity information recommending method and commodity information recommending system based on user historical behaviors
  • Commodity information recommending method and commodity information recommending system based on user historical behaviors

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[0056] The technical solutions of the embodiments of the present invention will be explained in detail below in conjunction with the drawings.

[0057] Such as figure 1 As shown, the method for recommending product information based on user historical behavior in this embodiment includes the following steps:

[0058] S11 collects user's historical behavior data on e-commerce websites. The historical behavior data includes user information and product information;

[0059] S12, according to the user's attributes, product characteristics and the user's historical behavior characteristics, establish the user product probability prediction feature vector;

[0060] S13 According to the user product probability prediction feature vector, train the model to obtain the user recommended product prediction model;

[0061] S14 Input the data into the user-recommended product prediction model to obtain the predicted purchase probability of the behavioral product;

[0062] S15 calculates the predicte...

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Abstract

The invention discloses a commodity information recommending method based on user historical behaviors. The method comprises the following steps of S11, acquiring historical behavior data of a user in an E-commerce website; S12, establishing a user commodity probability prediction characteristic vector according to the historical behavior data; S13, training a model according to the user commodity probability prediction characteristic vector, and obtaining a user recommendation commodity prediction model; S14, inputting to-be-predicated user data into the user recommendation commodity prediction model, and calculating a predicated purchasing probability of a behavior commodity; and S15, according to the predicated purchasing probability, calculating the predicated purchasing probabilities of correlated commodities, and combining the behavior commodities and the correlated commodities for obtaining a commodity recommending list. According to the commodity information recommending method and the commodity information recommending system, behavior data of the user are accurately analyzed; an individualized commodity recommending list is supplied to a user; and furthermore higher accuracy in commodity recommending is realized.

Description

technical field [0001] The present invention relates to a commodity information recommendation method and system in the field of electronic commerce, in particular, to a commodity information recommendation method and system based on user history behavior. Background technique [0002] The methods of using e-commerce user behavior to recommend products include: rankings based on user behavior (such as sales rankings), recommendations based on the same behavior (for example, when everyone saw product A at the same time, what other products did they see), and rankings based on the same theme Recommendations (such as children's mobile phone recommendations), recommendations based on user feedback (such as products that everyone likes), etc. By asking questions, customers answer questions, directly understand customer preferences, and recommend suitable products. In addition, there is a product recommendation method based on association rule equations. [0003] The above metho...

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Application Information

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IPC IPC(8): G06Q30/06G06F17/30
Inventor 孙奉海刘勇陈雪峰张侦
Owner 深圳市云网万店科技有限公司
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