Fusing Logical Relationship Information of Text in Neural Network for Text Classification
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-25
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1195966
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر