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Hadoop-based commodity recommendation system

A product recommendation and recommendation system technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as increased cost, undiscoverable, and increased difficulty of high-quality information

Inactive Publication Date: 2017-04-26
玺阅信息科技(上海)有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

It is very difficult for users to find suitable products among a large number of products. The traditional method is to classify products according to time, category, popularity and price, and provide target information and attributes known to users. Unknown but unknown Items of similar interest and their information
With the rapid growth of information volume, it is more difficult and costly to obtain high-quality information through users' active search or classified browsing

Method used

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Embodiment Construction

[0065] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further elaborated below in conjunction with illustrations and specific embodiments.

[0066] like figure 1 As shown, the product recommendation system based on Hadoop includes five layers: data access layer, data model layer, recommendation algorithm layer, recommendation engine layer and recommendation application layer; Interface interaction, so as to achieve high cohesion and low coupling of the system architecture, and has good scalability. The database of the system uses Hive; recommendation algorithms and recommendation engines can be added or deleted flexibly, and the system can control the different engines to recommend results. influences. Recommendation engines can also be combined to meet various recommendation needs of users. Different recommendation engines recommend different styles, and each user...

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Abstract

The invention provides a Hadoop-based commodity recommendation system comprising five layers: a data access layer, a data model layer, a recommendation algorithm layer, a recommendation engine layer, and a recommendation application layer. The insides of all layers employ modularization designs and all layers interact with each other based on interfaces, thereby realizing high cohesion and low coupling of the system architecture and high extensibility. The database of the system employs Hive; convenient on-line shopping functions like commodity browsing, purchasing payment, logistics allocation, after-sales service and the like can be provided for users. On the basis of the high-efficiency, reliable, and convenient-extension distributed system infrastructure, the system is suitable for large-scale data storage and computing processing; the system based on a novel design and a good design plan has the broad market promotion prospects.

Description

technical field [0001] The invention relates to a distributed system infrastructure system, in particular to a product recommendation system based on Hadoop. Background technique [0002] With the rapid development of the Internet, network technology is becoming more and more mature, and the cost is gradually reduced. In addition to traditional broadband services, major communication companies also provide high-speed, stable and relatively cheap mobile networks, which is conducive to the wide application of the network to all walks of life. It improves social productivity and facilitates people's lives. Driven by the software industry, the degree of enterprise informatization is getting higher and higher. The various network products and services provided cover people's basic necessities of life, food, housing, transportation, consumption and entertainment, which greatly facilitates people's lives. Manufacturers have launched mobile applications with different characteristi...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06F17/30
Inventor 潘岩
Owner 玺阅信息科技(上海)有限公司
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