Time sequence text feature extraction method and device, electronic equipment and storage medium
A feature extraction and timing technology, applied in the fields of electrical digital data processing, instruments, calculations, etc., can solve the problems of low data quality and data requirements, low feature extraction efficiency, high implementation complexity, etc., to achieve data quality and low data requirements , Improve the efficiency of feature extraction and reduce the amount of feature data
Pending Publication Date: 2022-04-15
北京网宿科技有限公司
View PDF0 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0003] In order to solve the problem that the existing time-series text feature extraction method based on the neural network model is not suitable for non-deep learning models, and the implementation complexity is high and the feature extraction efficiency is not high, the embodiment of this application provides a time-series text feature The extraction method, device, electronic equipment, and storage medium are applicable to non-deep learning machine learning models, and have low performance consumption, fast implementation speed, low data quality and data requirements, reduced implementation complexity and improved timing Text Feature Extraction Efficiency
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0094] In order to solve the problems in the background technology, the embodiments of the present application provide a time series text feature extraction method, device, electronic equipment and storage medium.
[0095] The preferred embodiments of the application will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the application, and are not used to limit the application, and in the absence of conflict, the application The embodiments and the features in the embodiments can be combined with each other.
[0096] The time-series text feature extraction method provided in the embodiment of the present application can be applied to a server or terminal device with computing functions. The server can be an independent physical server, or a cloud that provides basic cloud computing services such as cloud server, cloud database, and cloud storage. Serv...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More PUM
Login to View More Abstract
The invention discloses a time sequence text feature extraction method and device, electronic equipment and a storage medium, and solves the problems that an existing time sequence text feature extraction mode based on a neural network model is not suitable for a non-deep learning model, the implementation complexity is high, and the feature extraction efficiency is not high. Performing word segmentation on each time sequence text in the target time sequence text set, and counting the occurrence frequency of each word contained in the target time sequence text set in each time sequence text; determining the weight of each word in each time sequence text according to the occurrence frequency of each word in each time sequence text; for each word, determining the average weight of the word according to the weight of the word in each time sequence text; and obtaining a feature vector of each time sequence text according to the average weight of each word.
Description
technical field [0001] The present application relates to the field of natural language processing, and in particular to a time series text feature extraction method, device, electronic equipment and storage medium. Background technique [0002] In the field of Natural Language Processing (NLP), feature extraction for time-series texts is usually based on deep learning neural networks, such as word embedding, which is a numerical representation of words in the text. A word is mapped to a high-dimensional vector (word vector) to represent the word, for example, "machine learning" is expressed as [1, 2, 3], and "deep learning" is expressed as [2, 3, 3] , the word embedding algorithm can convert a sentence in the text into a high-dimensional matrix, and each word corresponds to a row of values. However, the method of using word embedding to extract temporal text features is usually carried out together as part of the deep learning neural network model (NLP task model), so that...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More Application Information
Patent Timeline
Login to View More Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/284G06F40/216
Inventor 刘卓龙
Owner 北京网宿科技有限公司