Contrasting Global and Refined Views for Author Name Disambiguation in Heterogeneous Networks
Resumo
Author Name Disambiguation (AND) as a clustering problem aims to correctly group publications sharing ambiguous author names into real author clusters. This work approaches the AND task using Heterogeneous Information Networks (HINs) to capture complex relationships between publications. Our method, AND-GloRe, employs a Graph Neural Network encoder trained via unsupervised contrastive learning to generate dual-view representations: a global view capturing overall relationships among publications, and a refined view capturing meta-path specific relationships. The effectiveness of our method is evaluated on the WhoIsWho datasets, achieving a pairwise F1-Score of 92.28%.
Palavras-chave:
Author Name Disambiguation, Contrastive Learning, Heterogeneous Information Network, Graph Neural Network
Referências
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Chen, B., Zhang, J., Zhang, F., Han, T., Cheng, Y., Li, X., Dong, Y., and Tang, J. (2023). Web-scale academic name disambiguation: The whoiswho benchmark, leaderboard, and toolkit. In KDD ’23, pages 3817–3828. ACM.
Chen, T., Kornblith, S., Norouzi, M., and Hinton, G. (2020). A simple framework for contrastive learning of visual representations. In 37th International Conference on Machine Learning, volume 119, pages 1597–1607. PMLR.
Cheng, Y., Chen, B., Zhang, F., and Tang, J. (2024). BOND: Bootstrapping from-scratch name disambiguation with multi-task promoting. In ACM Web Conference 2024, pages 4216–4226. ACM.
Cota, R. G., Gonçalves, M. A., and Laender, A. H. F. (2007). A heuristic-based hierarchical clustering method for author name disambiguation in digital libraries. In Anais do XXII SBBD, pages 20–34. SBC.
De Bonis, M., Falchi, F., and Manghi, P. (2023). Graph-based methods for author name disambiguation: a survey. PeerJ Computer Science, 9:e1536.
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Ferreira, A. A., Gonçalves, M. A., and Laender, A. H. F. (2020). Automatic Disambiguation of Author Names in Bibliographic Repositories. Springer International Publishing.
Han, H., Giles, L., Zha, H., Li, C., and Tsioutsiouliklis, K. (2004). Two supervised learning approaches for name disambiguation in author citations. In JCDL ’04, page 296–305. ACM.
Huang, J., Ertekin, S., and Giles, C. L. (2006). Efficient name disambiguation for large-scale databases. In Knowledge Discovery in Databases: PKDD 2006, pages 536–544. Springer Berlin Heidelberg.
Huang, Z., Zhang, H., Hao, C., Yang, H., and Wu, H. (2024). A cross-domain transfer learning model for author name disambiguation on heterogeneous graph with pretrained language model. Knowledge-Based Systems, 305:112624.
Hubert, L. and Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1):193–218.
Hussain, I. and Asghar, S. (2017). A survey of author name disambiguation techniques: 2010-2016. The Knowledge Engineering Review, 32:e22.
Levin, F. H. and Heuser, C. A. (2009). Evaluating the use of social networks in author name disambiguation in digital libraries. In Anais do XXIV SBBD, pages 46–60. SBC.
Liu, D., Zhang, R., Chen, J., and Chen, X. (2024). Author name disambiguation via paper association refinement and compositional contrastive embedding. In WWW ’24, page 2193–2203. ACM.
Ma, X., Wang, R., and Zhang, Y. (2019). Author name disambiguation in heterogeneous academic networks. In WISA, pages 126–137. Springer International Publishing.
Mikolov, T., Chen, K., Corrado, G. S., and Dean, J. (2013). Efficient estimation of word representations in vector space. In ICLR (Workshop Poster) 2013.
Pooja, K., Mondal, S., and Chandra, J. (2022). Exploiting higher order multi-dimensional relationships with self-attention for author name disambiguation. TKDD, 16(5).
Rehs, A. (2021). A supervised machine learning approach to author disambiguation in the web of science. Journal of Informetrics, 15(3):101166.
Rodrigues, N. S., Mariano, A. M., and Ralha, C. G. (2024). Author name disambiguation literature review with consolidated meta-analytic approach. IJDL, 25(4):765–785.
Wang, C., Pan, S., Hu, R., Long, G., Jiang, J., and Zhang, C. (2019). Attributed graph clustering: a deep attentional embedding approach. In IJCAI-19, page 3670–3676.
Wang, H., Wan, R., Wen, C., Li, S., Jia, Y., Zhang, W., and Wang, X. (2020). Author name disambiguation on heterogeneous information network with adversarial representation learning. In AAAI-20, volume 34, pages 238–245.
Xie, W., Liu, S., Wang, X., and Jia, T. (2022). Author name disambiguation via heterogeneous network embedding from structural and semantic perspectives. In ICTAI 2022, pages 245–250.
Ye, F., Xia, Z., Ling, Z., and Wu, L. (2025). Multi-view contrastive and cluster-guided learning for author name disambiguation. Expert Systems with Applications, 289:128324.
Yu, J., Ge, Q., Li, X., and Zhou, A. (2024). Heterogeneous graph contrastive learning with meta-path contexts and adaptively weighted negative samples. IEEE Transactions on Knowledge and Data Engineering, 36(10):5181–5193.
Zhang, Y., Zhang, F., Yao, P., and Tang, J. (2018). Name disambiguation in AMiner: Clustering, maintenance, and human in the loop. In KDD ’18, pages 1002–1011. ACM.
Zheng, X., Zhang, P., Cui, Y., Du, R., and Zhang, Y. (2021). Dual-channel heterogeneous graph network for author name disambiguation. Information, 12(383).
Zhou, A., Shi, M., and Yuan, R. (2024a). An effective author name disambiguation framework for large-scale publications. IEEE Access, 12:182086–182100.
Zhou, Q., Chen, W., Zhao, P.-P., Liu, A., Xu, J.-J., Qu, J.-F., and Zhao, L. (2024b). Towards effective author name disambiguation by hybrid attention. JCST, 39(4):929–950.
Bagga, A. and Baldwin, B. (1998). Entity-based cross-document coreferencing using the vector space model. In 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 1, pages 79–85. Association for Computational Linguistics.
Cappelli, F., Colavizza, G., and Peroni, S. (2025). Deep learning approaches to author name disambiguation: A survey. IJDL, 26(4):21.
Chen, B., Zhang, J., Zhang, F., Han, T., Cheng, Y., Li, X., Dong, Y., and Tang, J. (2023). Web-scale academic name disambiguation: The whoiswho benchmark, leaderboard, and toolkit. In KDD ’23, pages 3817–3828. ACM.
Chen, T., Kornblith, S., Norouzi, M., and Hinton, G. (2020). A simple framework for contrastive learning of visual representations. In 37th International Conference on Machine Learning, volume 119, pages 1597–1607. PMLR.
Cheng, Y., Chen, B., Zhang, F., and Tang, J. (2024). BOND: Bootstrapping from-scratch name disambiguation with multi-task promoting. In ACM Web Conference 2024, pages 4216–4226. ACM.
Cota, R. G., Gonçalves, M. A., and Laender, A. H. F. (2007). A heuristic-based hierarchical clustering method for author name disambiguation in digital libraries. In Anais do XXII SBBD, pages 20–34. SBC.
De Bonis, M., Falchi, F., and Manghi, P. (2023). Graph-based methods for author name disambiguation: a survey. PeerJ Computer Science, 9:e1536.
Elliott, S. (2010). Survey of author name disambiguation: 2004 to 2010. LPP, 443.
Ferreira, A. A., Gonçalves, M. A., and Laender, A. H. (2012). A brief survey of automatic methods for author name disambiguation. SIGMOD Rec., 41(2):15–26.
Ferreira, A. A., Gonçalves, M. A., and Laender, A. H. F. (2020). Automatic Disambiguation of Author Names in Bibliographic Repositories. Springer International Publishing.
Han, H., Giles, L., Zha, H., Li, C., and Tsioutsiouliklis, K. (2004). Two supervised learning approaches for name disambiguation in author citations. In JCDL ’04, page 296–305. ACM.
Huang, J., Ertekin, S., and Giles, C. L. (2006). Efficient name disambiguation for large-scale databases. In Knowledge Discovery in Databases: PKDD 2006, pages 536–544. Springer Berlin Heidelberg.
Huang, Z., Zhang, H., Hao, C., Yang, H., and Wu, H. (2024). A cross-domain transfer learning model for author name disambiguation on heterogeneous graph with pretrained language model. Knowledge-Based Systems, 305:112624.
Hubert, L. and Arabie, P. (1985). Comparing partitions. Journal of Classification, 2(1):193–218.
Hussain, I. and Asghar, S. (2017). A survey of author name disambiguation techniques: 2010-2016. The Knowledge Engineering Review, 32:e22.
Levin, F. H. and Heuser, C. A. (2009). Evaluating the use of social networks in author name disambiguation in digital libraries. In Anais do XXIV SBBD, pages 46–60. SBC.
Liu, D., Zhang, R., Chen, J., and Chen, X. (2024). Author name disambiguation via paper association refinement and compositional contrastive embedding. In WWW ’24, page 2193–2203. ACM.
Ma, X., Wang, R., and Zhang, Y. (2019). Author name disambiguation in heterogeneous academic networks. In WISA, pages 126–137. Springer International Publishing.
Mikolov, T., Chen, K., Corrado, G. S., and Dean, J. (2013). Efficient estimation of word representations in vector space. In ICLR (Workshop Poster) 2013.
Pooja, K., Mondal, S., and Chandra, J. (2022). Exploiting higher order multi-dimensional relationships with self-attention for author name disambiguation. TKDD, 16(5).
Rehs, A. (2021). A supervised machine learning approach to author disambiguation in the web of science. Journal of Informetrics, 15(3):101166.
Rodrigues, N. S., Mariano, A. M., and Ralha, C. G. (2024). Author name disambiguation literature review with consolidated meta-analytic approach. IJDL, 25(4):765–785.
Wang, C., Pan, S., Hu, R., Long, G., Jiang, J., and Zhang, C. (2019). Attributed graph clustering: a deep attentional embedding approach. In IJCAI-19, page 3670–3676.
Wang, H., Wan, R., Wen, C., Li, S., Jia, Y., Zhang, W., and Wang, X. (2020). Author name disambiguation on heterogeneous information network with adversarial representation learning. In AAAI-20, volume 34, pages 238–245.
Xie, W., Liu, S., Wang, X., and Jia, T. (2022). Author name disambiguation via heterogeneous network embedding from structural and semantic perspectives. In ICTAI 2022, pages 245–250.
Ye, F., Xia, Z., Ling, Z., and Wu, L. (2025). Multi-view contrastive and cluster-guided learning for author name disambiguation. Expert Systems with Applications, 289:128324.
Yu, J., Ge, Q., Li, X., and Zhou, A. (2024). Heterogeneous graph contrastive learning with meta-path contexts and adaptively weighted negative samples. IEEE Transactions on Knowledge and Data Engineering, 36(10):5181–5193.
Zhang, Y., Zhang, F., Yao, P., and Tang, J. (2018). Name disambiguation in AMiner: Clustering, maintenance, and human in the loop. In KDD ’18, pages 1002–1011. ACM.
Zheng, X., Zhang, P., Cui, Y., Du, R., and Zhang, Y. (2021). Dual-channel heterogeneous graph network for author name disambiguation. Information, 12(383).
Zhou, A., Shi, M., and Yuan, R. (2024a). An effective author name disambiguation framework for large-scale publications. IEEE Access, 12:182086–182100.
Zhou, Q., Chen, W., Zhao, P.-P., Liu, A., Xu, J.-J., Qu, J.-F., and Zhao, L. (2024b). Towards effective author name disambiguation by hybrid attention. JCST, 39(4):929–950.
Publicado
08/09/2026
Como Citar
LIMA, Victor Gonçalves; FORTES, Reinaldo Silva; FERREIRA, Anderson A..
Contrasting Global and Refined Views for Author Name Disambiguation in Heterogeneous Networks. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 359-372.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2026.249222.
