Abstract
As the number of published scientific papers continuously increases, the need to assess paper impact becomes more valuable than ever. In this work, we focus on citation-based measures that try to estimate the popularity (current impact) of an article. State-of-the-art methods in this category calculate estimates of popularity based on paper citation data. However, with respect to recent publications, only limited data of this type are available, rendering these measures prone to inaccuracies. In this work, we present ArtSim, an approach that exploits paper similarity, calculated using scholarly knowledge graphs, to better estimate paper popularity for recently published papers. Our approach is designed to be applied on top of existing popularity measures, to improve their accuracy. We apply ArtSim on top of four well-known popularity measures and demonstrate through experiments its potential in improving their popularity estimates.
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Notes
- 1.
Here we use similarity based on authors and topics as a proof of concept. However, our approach can be generalized using any other definition of article similarity.
- 2.
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Acknowledgments
We acknowledge support of this work by the project “Moving from Big Data Management to Data Science” (MIS 5002437/3) which is implemented under the Action “Re-inforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund). Icons in Fig. 1 were collected from www.flaticon.com and were made by Freepik, Good Ware and Pixel perfect.
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Chatzopoulos, S., Vergoulis, T., Kanellos, I., Dalamagas, T., Tryfonopoulos, C. (2020). ArtSim: Improved Estimation of Current Impact for Recent Articles. In: Bellatreche, L., et al. ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium. TPDL ADBIS 2020 2020. Communications in Computer and Information Science, vol 1260. Springer, Cham. https://doi.org/10.1007/978-3-030-55814-7_27
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