A Storm-based real-time recommendation method and a system therefor

A real-time recommendation and recommendation list technology, applied in the recommendation field, can solve the problems of poor real-time calculation of big data and achieve the effect of improving accuracy and quality

Inactive Publication Date: 2016-07-27
TCL CORPORATION
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  • Claims
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AI Technical Summary

Problems solved by technology

[0004] In view of the shortcomings of the prior art above, the purpose of the present invention is to provide a Storm-based real-time recommendation method and system to solve the problem of poor real-time performance of existing recommendation systems for big data calculations

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  • A Storm-based real-time recommendation method and a system therefor
  • A Storm-based real-time recommendation method and a system therefor
  • A Storm-based real-time recommendation method and a system therefor

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Embodiment Construction

[0040] The present invention provides a Storm-based real-time recommendation method and system. On the basis of the streaming computing framework Storm, by analyzing the time when the user uses the recommendation system, the user's context information (such as time and location) can be accurately understood, and Information modeling of user interests to analyze user interests and preferences, for example, the interests of users at work and after get off work are different, and the interests of users are different during weekdays and weekends; when making recommendations to users. Introduce the streaming computing framework Storm to collect user behavior logs in real time and analyze user interests, and calculate and generate recommendation lists based on context information to achieve efficient and real-time log data processing. In order to make the object, technical solution and effect of the present invention more clear and definite, the present invention will be further descr...

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Abstract

The invention provides a Storm-based real-time recommendation method and a system therefor. The real-time recommendation method comprises the steps of: A, performing offline similarity calculation on video data and behavior data of users separately to obtain a similarity model of video, and performing statistical analysis on the behavior data to obtain the statistical data of user behavior; B, performing user modeling according to the video data in the Storm end to generate interest vectors and combining the interest vectors and the similarity model to obtain individualized recommendation results based on the user behavior; C, integrating the statistical data, the similarity model and the individualized recommendation results to obtain a recommendation list. The method combines similarity and interest, thereby improving the accuracy of individualized analysis of user preferences and guaranteeing the recommendation quality.

Description

technical field [0001] The present invention relates to the technical field of recommendation, in particular to a Storm-based real-time recommendation method and system. Background technique [0002] With the development of information technology and the Internet, people have gradually entered the era of information overload from the era of information scarcity. In this era, both information consumers and information producers have encountered great challenges. As an information consumer, it is very difficult to find the information of interest from a large amount of information. As an information producer, how to make the information you produce stand out and be known by the majority of users is also very difficult. The existing recommendation system can solve the above problems. It models the user's interests by analyzing the user's historical behavior (such as watching, downloading, and collecting, etc.), so as to actively recommend information that can meet the user's ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 郑巧玲
Owner TCL CORPORATION
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