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Recommendation system building method based on cloud computing

A recommendation system and construction method technology, applied in computing, special data processing applications, instruments, etc., can solve problems such as inflexibility, high integration cost, and limit the large-scale application of recommendation systems, and achieve the effect of improving data processing efficiency.

Inactive Publication Date: 2011-08-31
SUZHOU LIANGJIANG TECH
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  • Description
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AI Technical Summary

Problems solved by technology

[0003] The current problems of the recommendation system are: 1. Not flexible enough; 2. Not fully considering business strategies; 3. Cannot adopt different recommendation strategies according to changes in recommendation requirements; 4. Difficult to handle large-scale data; Custom development, high integration cost, poor portability
These problems limit the large-scale application of recommender systems in practice
[0004] There are some challenges in the parallelism of cloud-based data mining algorithms

Method used

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  • Recommendation system building method based on cloud computing
  • Recommendation system building method based on cloud computing
  • Recommendation system building method based on cloud computing

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Embodiment Construction

[0020] The present invention will be further described below.

[0021] The e-commerce personalized recommendation system based on cloud computing includes a distributed file system layer, a distributed computing layer, a data analysis middleware layer, and a recommendation application layer. The distributed file system layer and the distributed computing layer are constructed using Hadoop, and The data analysis middleware layer is customized on the basis of Mahout according to business applications, and is accessed by users as a service. Each layer of the system has a corresponding cloud computing management module, including functions such as data security, resource monitoring, resource dynamic scheduling, resource dynamic deployment, resource planning and virtualization, to ensure that each layer has high reliability and scalability .

[0022] The inventive method mainly comprises the following contents:

[0023] (1) Build a distributed file system layer:

[0024] Build a...

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Abstract

The invention discloses a recommendation system building method based on cloud computing, which belongs to the field of cloud computing and recommendation system building. In the method, a Hadoop cloud platform with a plurality of nodes is built firstly; then a Mahout middleware is built on the Hadoop; a Mahout algorithm library is customized according to business demands; a traditional advancing algorithm, a pseudo-distributed advancing algorithm, and a distributed algorithm are realized on the Mahout middleware; and finally a recommended application framework is built according to the demands of users. With the invention, as a serial recommended algorithm and MapReduce are combined to realize a parallel algorithm, the processing efficiency can be effectively improved; a large quantity of data which can not be processed under the condition of using a single machine can be completed; and the recommendation results can be supplied to users very quickly.

Description

technical field [0001] The invention relates to a system construction method, in particular to a cloud computing-based recommendation system construction method, and belongs to the field of cloud computing and recommendation system construction. Background technique [0002] As e-commerce provides more and more choices, its structure becomes more and more complex, and users will get lost in a large amount of product information space, unable to find the products they need. One way to solve this problem is to develop an intelligent recommendation system to recommend products according to customers' preferences or needs to help customers complete the purchase process. At present, only a few large e-commerce websites (such as Amazon, eBay, etc.) have developed personalized recommendation systems for their own businesses, and most small and medium-sized enterprises do not have so much energy and resources to invest in building their own recommendation systems. [0003] The curr...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q30/00
Inventor 陈国庆邱飞
Owner SUZHOU LIANGJIANG TECH
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