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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 15: AAAI-21 Technical Tracks 15

Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification

February 1, 2023

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Authors

Hanqing Tao

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China


Shiwei Tong

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China


Kun Zhang

School of Computer Science and Information Engineering, Hefei University of Technology


Tong Xu

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China School of Data Science, University of Science and Technology of China


Qi Liu

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China School of Data Science, University of Science and Technology of China


Enhong Chen

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China School of Data Science, University of Science and Technology of China


Min Hou

Anhui Province Key Laboratory of Big Data Analysis and Application, University of Science and Technology of China School of Data Science, University of Science and Technology of China


DOI:

10.1609/aaai.v35i15.17637


Abstract:

Cognitive psychology research shows that humans have the instinct for abstract thinking, where association plays an essential role in language comprehension. Especially for Chinese, its ideographic writing system allows radicals to trigger semantic association without the need of phonetics. In fact, subconsciously using the associative information guided by radicals is a key for readers to ensure the robustness of semantic understanding. Fortunately, many basic and extended concepts related to radicals are systematically included in Chinese language dictionaries, which leaves a handy but unexplored way for improving Chinese text representation and classification. To this end, we draw inspirations from cognitive principles between ideography and human associative behavior to propose a novel Radical-guided Associative Model (RAM) for Chinese text classification. RAM comprises two coupled spaces, namely Literal Space and Associative Space, which imitates the real process in people's mind when understanding a Chinese text. To be specific, we first devise a serialized modeling structure in Literal Space to thoroughly capture the sequential information of Chinese text. Then, based on the authoritative information provided by Chinese language dictionaries, we design an association module and put forward a strategy called Radical-Word Association to use ideographic radicals as the medium to associate prior concept words in Associative Space. Afterwards, we design an attention module to imitate people's matching and decision between Literal Space and Associative Space, which can balance the importance of each associative words under specific contexts. Finally, extensive experiments on two real-world datasets prove the effectiveness and rationality of RAM, with good cognitive insights for future language modeling.

Topics: AAAI

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HOW TO CITE:

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification Proceedings of the AAAI Conference on Artificial Intelligence (2021) 13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification AAAI 2021, 13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou (2021). Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence, 13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. 2021. Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification. "Proceedings of the AAAI Conference on Artificial Intelligence". 13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. (2021) "Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification", Proceedings of the AAAI Conference on Artificial Intelligence, p.13898-13906

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou, "Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification", AAAI, p.13898-13906, 2021.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. "Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. "Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 13898-13906.

Hanqing Tao||Shiwei Tong||Kun Zhang||Tong Xu||Qi Liu||Enhong Chen||Min Hou. Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification. AAAI[Internet]. 2021[cited 2023]; 13898-13906.


ISSN: 2374-3468


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