Textual Analysis of ICALEPCS and IPAC Conference Proceedings: Revealing Research Trends, Topics, and Collaborations for Future Insights and Advanced Search
This work helps researchers and practitioners in the field understand research trends and prevent duplication, but it is incremental as it applies existing NLP methods to new conference data.
The authors performed a textual analysis of ICALEPCS and IPAC conference proceedings using natural language processing to extract topics, visualize trends, and analyze collaborations, providing a comprehensive overview of the research landscape and an advanced search tool for easier reference.
In this paper, we show a textual analysis of past ICALEPCS and IPAC conference proceedings to gain insights into the research trends and topics discussed in the field. We use natural language processing techniques to extract meaningful information from the abstracts and papers of past conference proceedings. We extract topics to visualize and identify trends, analyze their evolution to identify emerging research directions, and highlight interesting publications based solely on their content with an analysis of their network. Additionally, we will provide an advanced search tool to better search the existing papers to prevent duplication and easier reference findings. Our analysis provides a comprehensive overview of the research landscape in the field and helps researchers and practitioners to better understand the state-of-the-art and identify areas for future research.