User click information awarding method based on big data

Abstract

The invention provides a user click information awarding method based on big data. The user click information awarding method based on big data comprises the steps that information is pushed, and a user obtains an award according to the number of click times. Compared with the prior art, the user click information awarding method based on big data has the advantages that the demand of the user is analyzed by analyzing user data, the user needed information obtaining efficiency and information pushing efficiency are improved, a large amount of irrelevant information in browsing generated when the user searches for needed commodities in electronic commerce is avoided, and the electronic commerce efficiency is greatly improved; meanwhile, the use experience of the user is greatly improved, the user can be effectively guided for shopping, and the shopping experience of the user is met; at the same time, the user can obtain the corresponding award according to the number of click times, the desire of the user to click pushed information is further promoted, and commodities can be conveniently promoted.

Description

technical field [0001] The invention is a method for rewarding user click information based on big data, which belongs to the field of e-commerce. Background technique [0002] The Internet is like a double-edged sword, although to a large extent it promotes the rapid development of e-commerce, enabling merchants to display their products to consumers through e-commerce platforms, and consumers can fully understand the product information without leaving home. Grasp and conclude a transaction with the merchant, both parties get what they need, but with the continuous expansion of the scale of e-commerce, the number and types of goods increase rapidly, and customers need to spend a lot of time to find the goods they want to buy. [0003] This process of browsing a large amount of irrelevant information and products will undoubtedly cause consumers who are submerged in the problem of information overload to continue to lose. At the same time, as the e-commerce system is const...

AI Technical Summary

Problems solved by technology

[0002] The Internet is like a double-edged sword, although to a large extent it promotes the rapid development of e-commerce, enabling merchants to display their products to consumers through e-commerce platforms, and consumers can fully understand the product information without leaving home. Master and conclude a transaction with the merchant, both parties get what they need, but with the continuous expansion of e-commerce scale, the number and types of goods increase rapidly, customers need to spend a lot of time to find the goods they want to buy

[0003] This process of browsing a large amount of irrelevant information and products will undoubtedly lead to the loss of consumers who are submerged in the problem of information overload.

At the same time, as the e-commerce system is constantly expanding and the system structure is becoming more and more complex, the number of users and products is almost on a straight line. However, many recommendation algorithms at this stage have two problems due to their own constraints: Sparsity problem and scalability problem, which seriously affect the quality of recommendation

However, the influence of the specific environment on user interest is ignored in the current technology

On the other hand, in the face of a large number of resources, the existing scheme generates pushes based on users' evaluation information on resources. This kind of push based on page scores can only reflect the user's overall interest in the page.

However, in fact, the user's evaluation of the page resource is often generated according to its attributes, so the push results based only on the user's overall score on the resource are often one-sided.

[0005] Although big data technology can push product information to users, it cannot arouse the desire of users to click

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