Complex valued word vector construction method based on positions and semantics

A construction method and word vector technology, applied in the field of complex-valued vector construction based on location and semantics, can solve the problem of not making better use of complex-valued word vectors, and achieve the effect of overcoming the lack of text classification corpus

Pending Publication Date: 2020-02-28
TIANJIN UNIV
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Problems solved by technology

However, the current method only uses complex vectors, and does not make better use of co

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  • Complex valued word vector construction method based on positions and semantics
  • Complex valued word vector construction method based on positions and semantics
  • Complex valued word vector construction method based on positions and semantics

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[0052] The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the protection scope of the present invention is not limited to the following. figure 1 The flow of the neural network classification method based on the complex-valued vector representation of position and semantics proposed by this method is shown; figure 2 A possible distribution map of 3-dimensional plural word vectors is shown; image 3 The comparison results of the classification model running time of different word vectors are shown; Figure 4 It is a comparison chart of the similarity of different words under the same sentence for different word vectors. :

[0053] The extraction, sorting and processing of traditional webpage text content containing keywords is completely manual, laborious and labor-intensive, and with the explosive growth of webpage data, the manual method becomes inefficient. In this case, this system Use ...

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Abstract

The invention discloses a complex valued word vector construction method based on position and semantics, which comprises the following steps: searching a text classification corpus set, and dividingthe text classification corpus set into a training set, a verification set and a test set; preprocessing the text in the corpus set (removing stop words); constructing sentence representation by usingthe relative position information and the global semantic information; inputting the word vectors of the training corpus set into a complex-valued neural network, and training a semantic classification model; inputting the verification set text word vector into a complex-valued neural network model so as to calculate the prediction probability of each sample; testing the model obtained on the basis of the verification set on a test set; according to the method, the current situation that a text classification corpus set is relatively lacked is overcome, the feature information (position information) of the text can be extracted more fully, the position information and global semantic information of the text are fused, and the complex valued word vector is applied to the replicated neuralnetwork, so that neural network models have relatively strong discrimination capability.

Description

technical field [0001] The invention relates to the technical field of text classification, in particular to a method for constructing complex-valued vectors based on position and semantics. Background technique [0002] In the past few years, with the rapid development of science and technology, especially the rapid development of the Internet and social networks, all kinds of information are flooding the Internet, including comments and some of their own opinions published by users on social platforms. It has also become one of the main sources of information for users in their daily lives. People may obtain a large amount of information through the Internet, but how to manage these large amounts of information reasonably and effectively has become an issue that people are more and more concerned about. A very common management method for large amounts of information is classification, which shows that text classification contains huge social value. The present invention...

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Application Information

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IPC IPC(8): G06F16/35G06K9/62G06N3/04G06N3/08G06F16/383G06F16/387G06F40/289
CPCG06F16/35G06N3/084G06F16/383G06F16/387G06N3/044G06N3/045G06F18/214
Inventor 赵东浩张鹏
Owner TIANJIN UNIV
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