A network information retrieval method based on pre-classification and feature learning noise resistance

Abstract

The anti-noise network information retrieval method based on pre-classification and feature learning can be used for rapid retrieval of network information including text and image information. Firstly, a deep learning training network is used, a 16-layer deep neural network of VGG16 is selected, a rectification linear unit is used as an activation function, and a differential pressure layer is added after each complete connection layer. The number of nodes of the last completely connected layer is N, and a softmax function is used as a classification function of the last completely connectedlayer. After the network is trained, the data set extracts features in a forward propagation mode through the training network, a softmax is used for obtaining a pre-classification result from the last layer, and the data pre-classification result provides feedback information, namely the features belonging to the same category of network data should be stored together. And for the new query data,the similarity is measured between the query information and the information belonging to the same category in the query by using the cosine distance. The method has the advantages of high retrievalefficiency and high anti-noise performance.

Description

technical field [0001] The invention relates to a network information retrieval method based on pre-classification and feature learning and anti-noise, which can be widely used in the fields of network image search, text comparison, network public security and the like. It belongs to the field of machine learning and information processing. Background technique [0002] With the rapid development of Internet technology and cloud technology in recent years, network information has grown rapidly in an explosive manner. How to quickly and effectively retrieve the network information that users care about from these massive data has become a problem for researchers at home and abroad in recent years. popular research directions. Network information retrieval technology can be widely used in medical information retrieval, search engines, network security monitoring and other fields closely related to people's livelihood. [0003] At present, there are many methods for network i...

AI Technical Summary

Problems solved by technology

Although the content-based network information retrieval methods have achieved great results, these methods do not consider the distribution information of the data when extracting the characteristics of the network information. Information retrieval is very important

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