Zobrazeno 1 - 10
of 623
pro vyhledávání: '"Mayr Philipp"'
Publikováno v:
Journal of Data and Information Science, Vol 6, Iss 3, Pp 1-5 (2021)
Externí odkaz:
https://doaj.org/article/05ca3fb4525a45c185a4006bcf0be3cc
Autor:
Tong, Xu, Smirnova, Nina, Upadhyaya, Sharmila, Yu, Ran, Culbert, Jack H., Sun, Chao, Otto, Wolfgang, Mayr, Philipp
Objective: To explore and compare the performance of ChatGPT and other state-of-the-art LLMs on domain-specific NER tasks covering different entity types and domains in TCM against COVID-19 literature. Methods: We established a dataset of 389 article
Externí odkaz:
http://arxiv.org/abs/2408.13501
This study compares and analyses publication and document types in the following bibliographic databases: OpenAlex, Scopus, Web of Science, Semantic Scholar and PubMed. The results demonstrate that typologies can differ considerably between individua
Externí odkaz:
http://arxiv.org/abs/2406.15154
The study aims to highlight the growth and development of Indo-German collaborative research over the past three decades. Moreover, this study encompasses an in-depth examination of funding acknowledgements to gain valuable insights into the financia
Externí odkaz:
http://arxiv.org/abs/2404.17171
Autor:
Culbert, Jack, Hobert, Anne, Jahn, Najko, Haupka, Nick, Schmidt, Marion, Donner, Paul, Mayr, Philipp
OpenAlex is a promising open source of scholarly metadata, and competitor to the established proprietary sources, the Web of Science and Scopus. As OpenAlex provides its data freely and openly, it permits researchers to perform bibliometric studies t
Externí odkaz:
http://arxiv.org/abs/2401.16359
Autor:
Kartal, Yavuz Selim, Shahid, Muhammad Ahsan, Takeshita, Sotaro, Tsereteli, Tornike, Zielinski, Andrea, Zapilko, Benjamin, Mayr, Philipp
Publikováno v:
ECIR 2024 proceedings
The VADIS system addresses the demand of providing enhanced information access in the domain of the social sciences. This is achieved by allowing users to search and use survey variables in context of their underlying research data and scholarly publ
Externí odkaz:
http://arxiv.org/abs/2312.13423
Publikováno v:
Online Information Review 2024
Purpose: The recent proliferation of preprints could be a way for researchers worldwide to increase the availability and visibility of their research findings. Against the background of rising publication costs caused by the increasing prevalence of
Externí odkaz:
http://arxiv.org/abs/2308.04186
This demo paper presents UnScientify, an interactive system designed to detect scientific uncertainty in scholarly full text. The system utilizes a weakly supervised technique that employs a fine-grained annotation scheme to identify verbally formula
Externí odkaz:
http://arxiv.org/abs/2307.14236
Autor:
Smirnova, Nina, Mayr, Philipp
Acknowledgments in scientific papers may give an insight into aspects of the scientific community, such as reward systems, collaboration patterns, and hidden research trends. The aim of the paper is to evaluate the performance of different embedding
Externí odkaz:
http://arxiv.org/abs/2307.13377
Publikováno v:
2023
Retrievability measures the influence a retrieval system has on the access to information in a given collection of items. This measure can help in making an evaluation of the search system based on which insights can be drawn. In this paper, we inves
Externí odkaz:
http://arxiv.org/abs/2303.15036