Classification decision tree-based intelligent content distribution classification method

Abstract

The invention provides a classification decision tree-based intelligent content distribution classification method, and belongs to the field of content management systems and data mining. A universal system architecture for the method comprises a content data acquisition module, a classification strategy module and a classification decision tree training module. According to the method, a supervised learning method for machine learning is combined, existing content information in a content management system is used as a training dataset, and the training dataset is used for generating a classifier on the basis of a decision tree learning algorithm; all distributed contents are based on the same distribution way, and types of the distributed contents are determined by the classifier according to characteristic values of the distributed contents after the contents are distributed, so that the whole distribution process is finished. According to the method, user experiences in content distribution are improved; the types of the distributed contents are determined by the system rather than selected by a user, so that a distribution flow is more intelligent.

Description

technical field [0001] The invention belongs to the fields of content management system (Content Management System) and data mining (Data Mining). The classification decision tree configuration information generated by the content information is used to automatically and intelligently classify the newly released content of the user, so as to improve the user's content publishing experience under the premise of ensuring efficiency. Background technique [0002] With the widespread popularization of the Internet, especially the rapid development of social networks, not only the amount of network information has exploded, but also the types of content have become more abundant. For an enterprise, organization, or a social sharing platform in a broad sense, content management has new challenges, such as content storage, classification, retrieval, and so on. The present invention, however, focuses on the improvement of the distribution process of content management. In traditio...

AI Technical Summary

Problems solved by technology

These different ways of publishing have brought a lot of inconvenience: 1) From the perspective of front-end experience, users need to manually select content types, and the page needs to provide entry links for all types of content publishing; the more types, the more screens required The larger the space, the greater the impact on mobile smart terminals

2) From the perspective of engineering practice, providing specialized publishing processes for different types of content, the scalability of the architecture is poor, every time a type of content is added, the corresponding code must be added, and the business logic of different types of content publishing processes is basically Similar, easy to cause code redundancy

[0008] To sum up, in a rich-type content management system, the traditional content publishing process has a bad experience. If you encounter different types, you need to have its own specialized content publishing process, resulting in a bad front-end user experience and publishing Poor subsystem scalability and other deficiencies

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