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Deep learning-based experiential word vector and emotion classification method

A technology of deep learning and emotion classification, applied in neural learning methods, semantic analysis, special data processing applications, etc., can solve problems such as ignoring text emotional information

Inactive Publication Date: 2018-05-15
XIAN UNIV OF TECH
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Problems solved by technology

[0008] The purpose of the present invention is to provide a perceptual word vector and emotion classification method based on deep learning, which solves the problem that the existing word vector learning algorithm usually only uses the context of the word and ignores the emotional information of the text

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  • Deep learning-based experiential word vector and emotion classification method
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  • Deep learning-based experiential word vector and emotion classification method

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Embodiment Construction

[0061] The present invention will be described in detail below in combination with specific embodiments.

[0062] A perceptual word vector and emotion classification method based on deep learning of the present invention firstly minimizes the word context model, then adds emotional information to the processed word context model to construct a perceptual word vector, and finally , semi-supervised sentiment classification of review documents by active deep belief network method combined with perceptual word vectors.

[0063] Among them, the minimization process of the word context model is implemented according to the following steps:

[0064] Step 1, first construct the context model of the word, h i ={w i-c ,w i-c+1 ,...,w i-1 ,w i+1 ,...,w i+c-1 ,w i+c}; where w i Indicates the predicted target word with index i in the sentence, h i is a w in a sentence i context words for

[0065] Step 2. The feed-forward neural network composed of layer lookup→linear→hTanh→linea...

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Abstract

The invention discloses a deep learning-based experiential word vector and emotion classification method. A context model of a word is firstly built; then, emotion information is added to the contextmodel of the word to build an experiential word vector; and finally, through an active deep confidence network method and in combination of the experiential word vector, semi-supervised emotion classification on a comment document is carried out. The problem that the existing word vector learning algorithm generally only uses the context of the word but ignores the emotion information of the textis solved.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and relates to a perceptual word vector and a sentiment classification method based on deep learning. Background technique [0002] With the rapid development of information technology, network and information technology are rapidly affecting people's life at an unprecedented speed. At the same time, with the rise of social platforms such as Twitter, Facebook, and Weibo, and e-commerce platforms such as Amazon, JD.com, and Tmall, the number of commentary text resources on the Internet is increasing day by day. Faced with a large number of unstructured comment words and texts from these platforms, it is urgent to analyze and judge the emotional tendency expressed by user comment words through natural language processing technology. As a user, you can use the results of these perceptual analysis to expand your choices. Objects can also have a comprehensive understanding of cert...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/27G06N3/08
CPCG06N3/088G06F40/30G06F18/24G06F18/214
Inventor 姚全珠祝元勃费蓉张生杰
Owner XIAN UNIV OF TECH
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