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Stream-oriented recommended engine, recommendation system and recommendation method based on clustering

A recommendation engine and recommendation system technology, applied in relational databases, special data processing applications, instruments, etc., can solve the problem that the incremental matrix is ​​difficult to accurately summarize the relationship between users, so as to improve the domain characteristics and correlation characteristics, and improve the accuracy of recommendation. sexual effect

Active Publication Date: 2016-05-25
上海通创信息技术股份有限公司
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Problems solved by technology

The disadvantage of this method is that the calculated incremental matrix is ​​difficult to accurately summarize the relationship between users

Method used

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  • Stream-oriented recommended engine, recommendation system and recommendation method based on clustering
  • Stream-oriented recommended engine, recommendation system and recommendation method based on clustering
  • Stream-oriented recommended engine, recommendation system and recommendation method based on clustering

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Embodiment Construction

[0053] 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 described below in conjunction with specific illustrations.

[0054] see figure 1 , which shows the architecture diagram of the streaming recommendation engine based on clustering provided in this embodiment.

[0055] The recommendation engine constructs an incremental cluster and utilizes a cluster-based recommendation algorithm to perform personalized recommendations. As can be seen from the figure, the system architecture of this recommendation engine is divided into an offline computing layer 109 and a real-time computing layer 110, and mainly consists of three parts: the offline training model 101, the incremental training model 102, and the online recommendation module 103.

[0056]Among them, the offline training model 101, which runs in the offline computing layer 109 of the recommendation engine,...

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Abstract

The invention discloses a stream-oriented recommended engine, recommendation system and recommendation method based on clustering. According to the stream-oriented recommended engine, the recommendation system and the recommendation method based on clustering, an incremental clustering method is constructed in cooperation with advantages of a clustering structure and a collaborative filtering method, users and commodities are classified through the clustering structure, and the incidence relation between each user and the corresponding commodity is excavated based on the collaborative filtering method. By means of the stream-oriented recommended engine, the recommendation system and the recommendation method, the recommendation accuracy rate can be guaranteed, meanwhile the field characteristic and correlation characteristic of the recommendation result are improved, and recommendation accuracy is improved.

Description

technical field [0001] The invention relates to network data analysis and processing technology, in particular to a data information recommendation technology. Background technique [0002] At present, the industry's research on personalized recommendation technology mainly includes two methods based on collaborative filtering and matrix decomposition, while the incremental recommendation technology is mainly based on incremental matrix calculation methods. For the existing personalized recommendation system, there are deficiencies, as follows: [0003] The algorithm based on collaborative filtering mainly calculates users with similar preferences and similar items by analyzing the data set. The algorithm based on matrix decomposition mainly extracts the user's implicit preference through matrix decomposition, and obtains the final matrix through iterative calculation of the preference matrix. The advantage of these two methods is that the reliability of the calculation ha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/285G06F16/9535
Inventor 陈德来唐新怀陈越晨
Owner 上海通创信息技术股份有限公司
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