Streaming media content distribution method based on data feature dimension reduction coding

Abstract

The invention provides a streaming media content distribution method based on data feature dimension reduction coding, which comprises the following steps: step 1) extracting on-demand content data ofa server user, and performing historical content analysis to obtain a feature vector; 2) inputting the feature vector in the step 1) into a Word2Vec network, and training a content vector by using animproved Word2Vec model; wherein the improved Word2Vec model is obtained by training an original Word2Vec model and improving label data; 3) carrying out self-encoding training on the content vectorin the step 2) by utilizing a self-encoder model; 4) extracting an Encoder part in the auto-encoder model, and performing dimension reduction encoding on the content vector trained in the step 3) to generate a dimension reduction encoding content vector; and step 5) clustering the dimensionality reduction coding content vectors in the step 4) by using a k-means model, dividing the streaming mediacontent into n categories according to a clustering result, and respectively distributing the n categories to n edge servers of the corresponding content distribution network.

Description

technical field [0001] The present invention relates to the technical field of streaming media content distribution, content distribution network and deep learning algorithm, in particular to a streaming media content distribution method based on data feature dimensionality reduction coding. Background technique [0002] With the rapid development of Internet technology, 4G technology is gradually mature, and 5G technology is coming soon. The content of network resources is also becoming more and more abundant, especially streaming media content based on network TV and network video makes the pressure of Internet bandwidth more and more serious. Content delivery network (CDN) has greatly improved the service quality of streaming media content and user experience. However, CDNs also have limitations. Due to the limited storage capacity of the edge server, it cannot store all network resources. Whether the streaming media content stored in the edge server is suitable and mee...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the above-mentioned problems in the existing streaming media content distribution method. The present invention provides a streaming media content distribution method based on data feature dimensionality reduction coding, which utilizes the user's browsing record data in the network , use the Word2Vec model and autoencoder model in the deep learning model, and the K-means model in the traditional machine learning, to improve the distribution accuracy of the distributed content and improve the clustering accuracy

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