Knowledge base processing method based on text classification algorithm

Baisheng Zhong and Mohd Shamrie Sainin and Tan Soo Fun (2023) Knowledge base processing method based on text classification algorithm. In: 5th IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 12 - 14 Septrmber 2023, Kota Kinabalu, malaysia.

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Abstract

The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. In practical application, the knowledge base processing method has been prove to have a good performance in text classification tasks. The utilization of knowledge base processing method in text classification has led to an average accuracy improvement of more than 17%. Furthermore, this method significantly reduces labeling costs by approximately 70% compared to traditional approaches. Recently, knowledge base processing methods have been widely used in supporting business applications, social media analysis and other fields. This paper proposes a knowledge base method to establish a feature model related to domain speciality and combine it with traditional text classification algorithm, so as to optimize the training and reasoning process of the classification model and improve the accuracy of classification effect. Lastly, we suggested strategies to overcome the shortcoming of the knowledge base method in improving the construction and training of the classification model.

Item Type:	Conference or Workshop Item (Other)
Keyword:	Domain specialty, Characteristic model, Traditional classification algorithm, Classification effect
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science > QA76.75-76.765 Computer software T Technology > TD Environmental technology. Sanitary engineering > TD1-1066 Environmental technology. Sanitary engineering > TD172-193.5 Environmental pollution
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	JUNAINE JASNI -
Date Deposited:	08 Aug 2025 16:10
Last Modified:	08 Aug 2025 16:18
URI:	https://eprints.ums.edu.my/id/eprint/44799

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