Important citations identification with semi-supervised classification model

Author:

An Xin,Sun Xin,Xu ShuoORCID

Funder

national natural science foundation of china

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Science Applications,General Social Sciences

Reference44 articles.

1. Abu-Jbara, A., Ezra, J., & Radev, D. (2013). Purpose and polarity of citation: Towards NLP-based bibliometrics. In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 596–606).

2. Aljuaid, H., Iftikhar, R., Ahmad, S., Asif, M., & Afzal, M. T. (2021). Important citation identification using sentiment analysis of in-text citations. Telematics and Informatics, 56, 101492.

3. An, X., Sun X., Xu, S. (2021b). Important citations identification with semi-supervised classification model. The first Workshop on AI + Informetrics at the iConference 2021.

4. An, X., Sun, X., Xu, S., Hao, L., & Li, J. (2021a). Important citations identification by exploiting generative model into discriminative model. Journal of Information Science. https://doi.org/10.1177/0165551521991034

5. Bennett, K., & Demiriz, A. (1999). Semi-supervised support vector machines. Advances in Neural Information Processing Systems, 368–374.

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