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Design and implementation of an academic expert system through big data analysis

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Abstract

Most researchers establish research directions in their study of new fields by providing expert advice or publishing expert papers. The existing academic search services display papers by field but do not provide experts by field. Therefore, researchers are left to judge experts in each field by analyzing the papers for themselves. In this paper, we design and implement an expert search system based on papers that have been published in the academic societies. The academic expert search system is based on a big data processing system to handle a large amount of data in academic fields. It calculates an expert score using quality and influence factors. The quality factor is calculated based on the citations, impact factor, and recentness of a paper. The influence factor is measured by the sparsity of a field and the degree of contributiveness of an author. The proposed system provides various services such as expert searches, keyword searches, the hot topics, expert relationships, and academic society statistics. By finding experts in a specific field, our system can support researchers’ research activities.

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Acknowledgments

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2019R1A2C2084257, NRF-2017S1A5B8059946), by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. B0101-15-0266, Development of High Performance Visual BigData Discovery Platform for Large-Scale Realtime Data Analysis), by the AURI (Korea Association of University, Research institute and Industry) grant funded by the Korea Government (MSS : Ministry of SMEs and Startups). (No. S2929950, HRD program for 2020), by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2020-0-01462) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation).

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Authors and Affiliations

  1. School of Information and Communication Engineering, Chungbuk National University, Chungdae-ro 1, Seowon-Gu, Cheongju, Chungbuk, 28655, Korea

    Dojin Choi, Hyeonbyeong Lee & Jaesoo Yoo

  2. Department of Software Convergence, Wonkwang University, Iksan, Korea

    Kyoungsoo Bok

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  1. Dojin Choi
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  2. Hyeonbyeong Lee
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  4. Jaesoo Yoo
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Correspondence to Jaesoo Yoo.

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Choi, D., Lee, H., Bok, K. et al. Design and implementation of an academic expert system through big data analysis. J Supercomput 77, 7854–7878 (2021). https://doi.org/10.1007/s11227-020-03446-0

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