Topic Term Clustering Based on Semi-supervised Co-occurrence Graph and Its Application in Chinese Judgement Documents

Author:

Yang Xin,Weng Yang,Chen Baogui

Publisher

Springer Nature Singapore

Reference11 articles.

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3. Yang, S., Huang, G., Cai, B.: Discovering topic representative terms for short text clustering. IEEE Access 7, 92037–92047 (2019)

4. Fang, Y., et al.: Few-shot learning for Chinese legal controversial issues classification. IEEE Access 8, 75022–75034 (2020)

5. Tian, X., et al.: K-means clustering for controversial issues merging in Chinese legal texts. In: Legal Knowledge and Information Systems, vol. 313 (2018)

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