EGU24-7570, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-7570
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Navigating the Academic Landscape: Intelligent Retrieval Systems for Geoscience Exploration

Yi Xu, Cheng Deng, Shuchen Cai, Bo Xue, and Xinbing Wang
Yi Xu et al.
  • Shanghai Jiao Tong University, China (yixu98@sjtu.edu.cn)

The surge in academic publications mirrors the evolutionary strides of human civilization, marked by an exponential growth in their numbers. Addressing the lacuna in well-organized academic retrieval systems for geoscientists, the Geo-Literature system emerges as a transformative tool. This system, boasting a vast repository of over seven million papers and information on four million scholars, employs cutting-edge technology to reshape the landscape of academic search, analysis, and visualization within the geoscience domain.

Driven by the necessity to bridge the gap between modeling frameworks and geological constraints, Geo-Literature incorporates geoscience knowledge mining and representation technologies. Through its intelligent update and fusion system, it not only integrates new publications but also analyzes language, space, and time relationships, effectively overcoming challenges posed by knowledge ambiguity. The platform's geoscience knowledge interaction and presentation technology facilitate intelligent retrieval, recommendation systems, and the creation of comprehensive scholarly portraits.

The impact of Geo-Literature transcends conventional academic boundaries. Establishing associations, mapping key attributes, and providing hierarchical visualizations, the system assists researchers in uncovering knowledge and forming a nuanced understanding of the academic space in geosciences. Consequently, Geo-Literature not only enhances the efficiency of paper retrieval but also contributes to broader scientific goals by fostering interdisciplinary collaboration and advancing our comprehension of Earth's deep-time processes.

How to cite: Xu, Y., Deng, C., Cai, S., Xue, B., and Wang, X.: Navigating the Academic Landscape: Intelligent Retrieval Systems for Geoscience Exploration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7570, https://doi.org/10.5194/egusphere-egu24-7570, 2024.