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Network consumption system

A kind of network and system technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as time-consuming, recommendation algorithms are difficult to provide consumer recommendation services, and a lot of time is spent, so as to achieve the effect of improving efficiency

Inactive Publication Date: 2015-12-16
上海研深信息科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

With the expansion of the e-commerce system scale and the increasingly complex consumer demand, it is becoming more and more difficult for traditional recommendation algorithms to provide recommendation services that satisfy consumers.
[0004] The library plays a huge role as a source of knowledge for students, but it is very time-consuming to go to the library to choose books, because there are too many books and categories, it often takes a lot of time to find the books you need

Method used

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  • Network consumption system

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Embodiment

[0021] Such as figure 1 As shown, the figure includes a foreground module and a background module. The foreground module includes a system recommendation submodule, a personalized recommendation submodule, a user browsing record submodule, a book browsing ranking submodule, and a bibliography retrieval submodule. The background module includes The book information management module, the user information management module, the book category management module, and the school subject management module, the foreground module and the background module are all controlled by a CPU.

[0022] The system recommendation sub-module is realized by asp.net and AJAX technology, and the system realizes the comprehensive analysis of the preference of the consumer groups of the website users by analyzing the interests and hobbies of most users and the browsing times of book information, which is the first time for those who use this system Users recommend recent most popular books and best-sell...

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PUM

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Abstract

The invention relates to a network consumption system which comprises a foreground module and a background module. The foreground module comprises a system recommending submodule, an individualized recommending submodule, a user browsing recording submodule, a book browsing ranking submodule and a bibliography retrieval submodule. The background module comprises a book information management module, a user information management module, a book class management module and a school subject specialty management module. The foreground module and the background module are controlled by a central processing unit (CPU). The network consumption system can preferentially book information which satisfies a customer preference in a database to the customer, thereby realizing a purpose of improving book information retrieval efficiency of the customer.

Description

technical field [0001] The invention relates to a network consumption system. Background technique [0002] In order to solve the problem of Internet information overload and reduce consumers' search costs, recommender systems, as a typical information overload technology, have been widely used in e-commerce systems. [0003] In the traditional shopping environment, in view of the dynamic shift of consumers' consumption preferences, salespersons usually recommend products to consumers based on their purchase history and current purchase interests. In the network environment, the shopping assistant with the recommendation function as the core reduces the search cost of online consumers to a certain extent, but the recommendation algorithm adopted only uses the user's historical rating of the product as the recommendation basis, ignoring the consumer's consumption preference The characteristics of dynamic transfer. With the expansion of e-commerce system scale and the increa...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q30/02
Inventor 赵玉荣
Owner 上海研深信息科技有限公司
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