SBBD

Paper Registration

1

Select Book

2

Select Paper

3

Fill in paper information

4

Congratulations

Fill in your paper information

English Information

(*) To change the order drag the item to the new position.

Authors
# Name
1 Geiza da Silva(geiza.hamazaki@uniriotec.br)
2 Elvismary de Armas(earmas@inf.puc-rio.br)
3 Pedro Saieg(pedrosf@tecgraf.puc-rio.br)
4 Rafael de Castro(rayrescastro@tecgraf.puc-rio.br)
5 Thiago Coqueiro(thiagodamicoc@tecgraf.puc-rio.br)
6 Melissa Lemos(melissa@tecgraf.puc-rio.br)
7 Liester Castro(liester@tecgraf.puc-rio.br)

(*) To change the order drag the item to the new position.

Reference
# Reference
1 Bonatti, P. A., Decker, S., Polleres, A., and Presutti, V. (2019). Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371). Dagstuhl Reports, 8(9):29–111.
2 Brewton, B. (2023). How Using Knowledge Graphs can Optimize the Oil and Gas Industry. https://www.linkedin.com/pulse/ how-using-knowledge-graphs-can-optimize-oil-gas-industry\ -jon-brewton#. Acessado em 27/06/2025.
3 Cao, L., Sun, J., and Cross, A. (2024). An automatic and end-to-end system for rare disease knowledge graph construction based on ontologies-enhanced large language models. https://arxiv.org/abs/2403.00953. Acessado em 27/06/2025.
4 Carta, S., Giuliani, A., Manca, M. M., Piano, L., and Tiddia, S. G. (2024). Towards zeroshot knowledge graph building: Automated schema inference. In Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, page 467–473. Association for Computing Machinery.
5 Cremaschi, M., D’Adda, F., and Maurino, A. (2025). steellm: An llm for generating semantic annotations of tabular data. ACM Trans. Intell. Syst. Technol. Just Accepted.
6 Ehrlinger, L. and Woß, W. (2016). Towards a definition of knowledge graphs. In Martin, ¨ M., Cuquet, M., and Folmer, E., editors, Joint Proceedings of the Posters and Demos Track of the 12th International Conference on Semantic Systems - SEMANTiCS2016, volume 1695 of CEUR Workshop Proceedings.
7 Huang, S., Wang, Y., and Yu, X. (2020). Design and implementation of oil and gas information on intelligent search engine based on knowledge graph. Journal of Physics: Conference Series, 1621:012010,
8 Korinek, A. (2023). Language models and cognitive automation for economic research. Working Paper 30957, National Bureau of Economic Research. Acessado em 27/06/2025.
9 Moor, M., Banerjee, O., Abad, Z. S. H., Krumholz, H. M., Leskovec, J., Topol, E. J., and Rajpurkar, P. (2023). Foundation models for generalist medical artificial intelligence. Nature, 616(7956):259–265.
10 Sequeda, J., Allemang, D., and Jacob, B. (2025). Knowledge graphs as a source of trust for llm-powered enterprise question answering. Journal of Web Semantics, 85:100858.
11 Song, S., Yang, C., Xu, L., Shang, H., Li, Z., and Chang, Y. (2024). Travelrag: A tourist attraction retrieval framework based on multi-layer knowledge graph. ISPRS International Journal of Geo-Information, 13(11).
12 Tupayachi, J., Xu, H., Omitaomu, O. A., Camur, M. C., Sharmin, A., and Li, X. (2024). Towards next-generation urban decision support systems through ai-powered construction of scientific ontology using large language models—a case in optimizing intermodal freight transportation. Smart Cities, 7(5):2392–2421.
13 Zheng, T., Deng, Z., Tsang, H. T., Wang, W., Bai, J., Wang, Z., and Song, Y. (2025). From automation to autonomy: A survey on large language models in scientific discovery. https://arxiv.org/abs/2505.13259. Acessado em 27/06/2025.