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English Information

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Authors
# Name
1 Eduardo de Souza(eduardomoreirafds@gmail.com)
2 Anderson Rossanez(anderson.rossanez@ic.unicamp.br)
3 Julio Dos Reis(jreis@ic.unicamp.br)
4 Ricardo Torres(ricardo.dasilvatorres@wur.nl)

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Reference
# Reference
1 Arnaout, H. and Elbassuoni, S. (2018). Effective Searching of RDF Knowledge Graphs. Journal of Web Semantics, 48:66–84.
2 Beck, F., Burch, M., Diehl, S., and Weiskopf, D. (2017). A Taxonomy and Survey of Dynamic Graph Visualization. Computer Graphics Forum, 36(1):133–159.
3 Chen, F., Doan, A., Yang, J., and Ramakrishnan, R. (2008). Efficient Information Extraction over Evolving Text Data. In 2008 IEEE 24th International Conference on Data Engineering, pages 943–952.
4 Hogan, A., Blomqvist, E., Cochez, M., D’amato, C., Melo, G. D., Gutierrez, C., Kirrane, S., Gayo, J. E. L., Navigli, R., Neumaier, S., Ngomo, A.-C. N., Polleres, A., Rashid, S. M., Rula, A., Schmelzeisen, L., Sequeda, J., Staab, S., and Zimmermann, A. (2021). Knowledge Graphs. ACM Comput. Surv., 54(4).
5 Kim, H. (2017). Towards a Sales Assistant Using a Product Knowledge Graph. Journal of Web Semantics, 46-47:14–19.
6 Liu, J., Zhang, Q., Fu, L., Wang, X., and Lu, S. (2019). Evolving Knowledge Graphs. In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, pages 2260–2268.
7 Pernischov ́a, R., Dell’Aglio, D., Horridge, M., Baumgartner, M., and Bernstein, A. (2019). Toward Predicting Impact of Changes in Evolving Knowledge Graphs. In SEMWEB.
8 Pomp, A., Kraus, V., Poth, L., and Meisen, T. (2020). Semantic Concept Recommendation for Continuously Evolving Knowledge Graphs. In Filipe, J., ́Smiałek, M., Brodsky, A., and Hammoudi, S., editors, Enterprise Information Systems, pages 361–385, Cham. Springer International Publishing.
9 Rospocher, M., van Erp, M., Vossen, P., Fokkens, A., Aldabe, I., Rigau, G., Soroa, A., Ploeger, T., and Bogaard, T. (2016). Building Event-Centric Knowledge Graphs from News. Journal of Web Semantics, 37-38:132–151.
10 Rossanez, A. and Dos Reis, J. C. (2019). Generating Knowledge Graphs from Scientific Literature of Degenerative Diseases. In Proceedings of the 4th International Workshop on Semantics-Powered Data Mining and Analytics, SEPDA 2019, pages 12–23.
11 Rossanez, A., Dos Reis, J. C., Torres, R. d. S., and De Ribaupierre, H. (2020). KGen: A Knowledge Graph Generator from Biomedical Scientific Literature. BMC Medical Informatics and Decision Making, 20(S4).
12 Rossanez, A., Dos Reis, J. C., and Torres, R. d. S. (2020). Representing Scientific Literature Evolution via Temporal Knowledge Graphs. In Proceedings of the 6th Workshop on Managing the Evolution and Preservation of the Data Web, MEPDaW 2020, pages 33–42.
13 Singh, K., Lytra, I., Radhakrishna, A. S., Shekarpour, S., Vidal, M.-E., and Lehmann, J. (2020). No one is Perfect: Analysing the Performance of Question Answering Components over the dbpedia Knowledge Graph. Journal of Web Semantics, 65:100594.
14 Tosi, M. D. L. and dos Reis, J. C. (2022). Understanding the Evolution of a Scientific Field by Clustering and Visualizing Knowledge Graphs. Journal of Information Science, 48(1):71–89.
15 Uchoa Maia Rodrigues, D. C., Moura, F. A., Cunha, S. A., and da S. Torres, R. (2019). Graph Visual Rhythms in Temporal Network Analyses. Graphical Models, 103:101021.