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Fusing Logical Relationship Information of Text in Neural Network for Text Classification
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-25
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
With the development of computer science and information science, text classification technology has been greatly developed and its application scenarios have been widened.
In traditional process of text classification, the existing method will lose much logical relationship information of text.
The logical relationship information of a text refers to the relationship information among different logical parts of the text, such as title, abstract, and body.
When human beings are reading, they will take title as an important part to remind the central idea of the article, abstract as a brief summary of the content of the article, and body as a detailed description of the article.
In most of the text classification studies, researchers concern more about the relationship among words (word frequency, semantics, etc.) and neglect the logical relationship information of text.
It will lose information about the relationship among different parts (title, body, etc.) and have an influence on the performance of text classification.
Therefore, we propose a text classification algorithm—fusing the logical relationship information of text in neural network (FLRIOTINN), which complements the logical relationship information into text classification algorithms.
Experiments show that the effect of FLRIOTINN is better than the conventional backpropagation neural networks which does not consider the logical relationship information of text.
American Psychological Association (APA)
Wang, Heyong& Zeng, Dehang. 2020. Fusing Logical Relationship Information of Text in Neural Network for Text Classification. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1195966
Modern Language Association (MLA)
Wang, Heyong& Zeng, Dehang. Fusing Logical Relationship Information of Text in Neural Network for Text Classification. Mathematical Problems in Engineering No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1195966
American Medical Association (AMA)
Wang, Heyong& Zeng, Dehang. Fusing Logical Relationship Information of Text in Neural Network for Text Classification. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1195966
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195966