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Chinese financial news text classification method based on convolutional neural network

A convolutional neural network and text classification technology, applied in the field of computer natural language processing, can solve the problems of disorganized news data, lack of automatic and efficient management, etc.

Pending Publication Date: 2018-08-14
SHANGHAI UNIV
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Problems solved by technology

[0016] The purpose of the present invention is to provide a method for classifying Chinese financial news based on convolutional neural networks in order to solve the problems of disorganized news data and lack of automatic and efficient management in the current financial field.

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  • Chinese financial news text classification method based on convolutional neural network
  • Chinese financial news text classification method based on convolutional neural network
  • Chinese financial news text classification method based on convolutional neural network

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Embodiment Construction

[0045] Preferred embodiments of the present invention are described as follows in conjunction with the accompanying drawings:

[0046] like figure 1As shown, a Chinese financial news text classification method based on convolutional neural network, using a large-scale financial news corpus, through the method of unsupervised learning, training to obtain a generalized and general financial word vector model, and effectively convert the word vector Introduced into the training of the convolutional neural network model, the statistical information of the model is increased by dynamically adjusting the word vector.

[0047] This example collects a total of 280,000 pieces of latest financial information on the 7*24-hour platform of Sina Finance; collects Baidu Encyclopedia content of 12,965 financial-related words in the Sogou thesaurus; There are a total of 2,768 stock-related profiles and Baidu Encyclopedia content on the board.

[0048] 1) Word vector training: use the neural ...

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Abstract

The invention discloses a Chinese financial news text classification method based on a convolutional neural network. The method is mainly divided into four parts including word vector training, text preprocessing, neural network model training and news classification. Large-scale financial news corpora are used for training to obtain a broadly common financial-category word vector model through anunsupervised learning method, the word vector is effectively imported into the training of the convolutional neural network, and the statistical information of the model is increased through a methodof dynamically regulating the word vector. The adopted convolutional neural network has a simple structure, and can show excellent performances by aiming at a small sample set, so that a Chinese financial news text classification problem can be effectively solved, and effectiveness of the convolutional neural network in processing a text classification problem can be fully proved.

Description

technical field [0001] The invention relates to the field of computer natural language processing, in particular to a method for classifying Chinese financial news texts based on a convolutional neural network. Background technique [0002] The content of financial news covers all areas related to the economy, from production to consumption, from rural areas to cities, from micro to macro, from economic work to social and political life, etc. Concise text covers a large amount of information. At the same time, due to the emergence of the Internet, its transmission speed has been rapidly increased, and readers can learn relevant information at the first time. Especially for entrepreneurs and investors, financial news is an important basis for judging market changes . However, in the face of the explosive and disorderly growth of news data, it is more difficult for users to obtain useful information year-on-year. There is an urgent need to classify the positive and negative o...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/35G06F40/289
Inventor 吴佳萍谢志峰黄东晋丁友东
Owner SHANGHAI UNIV
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