Hadoop cloud platform-based Web resource personalized recommendation system and method
A recommendation system and cloud platform technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of huge data volume and difficult calculation process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2017-03-15
- Estimated Expiration
- Not applicable · inactive patent
Smart Images

Figure 1 
Figure 2 
Figure 3
Abstract
Description
technical field
[0001] The invention relates to the technical field of resource recommendation systems, in particular to a Hadoop cloud platform-based Web resource personalized recommendation system and method. Background technique
[0002] With the rapid development of the Internet, the web resources in the network are growing explosively. Users are often at a loss when faced with such a large number of resources, and it takes a lot of time to find the information they want. As an important means of information filtering, personalized recommendation is an effective way to solve the current information overload problem, so it is necessary to make appropriate personalized recommendations for users. However, in real life, due to the large amount of data, the calculation process is very difficult, and we cannot easily obtain the results we need. The emergence of cloud computing technology provides us with a good method, so that we can better use the distributed computing envir...
Examples
Embodiment Construction
[0125] Such as Figure 1-Figure 5 as shown, Figure 1-Figure 5 A personalized recommendation system based on Hadoop cloud platform Web resources proposed by the present invention.
[0126] refer to Figure 1-Figure 5, the personalized recommendation system based on Hadoop cloud platform Web resources that the present invention proposes, comprises:
[0127] The user model module is used to collect the browsing behavior information of the user on the web resource page, and calculate the user's interest in the above web resource page according to the above browsing behavior information of the user;
[0128] The recommendation algorithm module, according to the degree of interest calculated by the user model module, uses the recommendation algorithm to cluster the collected user browsing behavior information on the Web resource page to obtain the clustering results, and then constructs a matrix based on the above clustering results, and then passes Analyze the matrix constructe...