Short text classification method based on deep neural mapping support vector machine

Abstract

The invention discloses a short text classification method based on a deep neural mapping support vector machine, and belongs to the field of text classification and deep learning. A short text classification algorithm combining a convolutional neural network and the deep neural mapping support vector machine (DNMSVM) is provided for solving the problems that Softmax is adopted as a classifier forthe convolutional neural network, the generalization capability is insufficient, feature extraction and kernel function learning are needed for directly using the support vector machine for classification and the optimal solution is often difficult to achieve, and thus the classification effect on short text is improved. By means of the method, complex preprocessing of the text is not needed, theaccuracy is high, and the reliability and robustness are improved.

Description

technical field [0001] The invention belongs to the field of text classification and deep learning, and relates to a short text classification method based on a deep neural mapping support vector machine, which can be used for short text classification or emotion classification such as movie evaluation and commodity evaluation. Background technique [0002] In recent years, with the rapid development of computer technology, the Internet, and the mobile Internet, the number of Internet users has shown explosive growth. A large number of active users generate a large number of short texts (ShortText) on various information interaction platforms every day, and these short texts It involves various fields of people's daily life, such as product review (Product Review), movie review (Movie Review), and web page information retrieval (Web Information Retrival). Massive texts contain a lot of information to be mined. This is a hot research topic in the field of machine learning in ...

AI Technical Summary

Problems solved by technology

The key step in the text classification task is feature representation. Most of the traditional feature representation methods are based on the bag of words model, and these methods often ignore the context information of the text or the order in which words appear in the text.

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