Analyzing the research landscape of DaWaK papers from 1999 to 2019

Tatsawan Timakum; Soobin Lee; Il Yeol Song; Min Song

doi:10.1007/978-3-030-59065-9_1

Analyzing the research landscape of DaWaK papers from 1999 to 2019

Tatsawan Timakum, Soobin Lee, Il Yeol Song, Min Song

Department of Library and Information Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The International Conference on Big Data Analytics and Knowledge Discovery (DaWaK) has become a key conduit to exchange experience and knowledge among researchers and practitioners in the field of data warehousing and knowledge discovery. This study has quantitatively analyzed the 775 papers published in DaWaK from 1999 to 2019. This study presents the knowledge structure of the DaWaK papers and identifies the evolution of research topics in this discipline. Several text mining techniques were applied to analyze the contents of the research fields and to structure the knowledge presented at DaWaK. Dirichlet Multinomial Regression (DMR) is used to examine the trend of the research topics. Research metrics were used to identify conference and paper performance in terms of citation counts, readers, and the number of downloads. The study shows that DaWaK research outcomes have been receiving consistent attention from the scholarly community in the past 21 years. The 775 papers were cited by 4,339 times, marking the average number of citations of each proceeding as 207 times, and the average number of citations per published paper as six times.

Original language	English
Title of host publication	Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings
Editors	Min Song, Il-Yeol Song, Gabriele Kotsis, Ismail Khalil, A Min Tjoa
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3-13
Number of pages	11
ISBN (Print)	9783030590642
DOIs	https://doi.org/10.1007/978-3-030-59065-9_1
Publication status	Published - 2020
Event	22nd International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2020 - Bratislava, Slovakia Duration: 2020 Sept 14 → 2020 Sept 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12393 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	22nd International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2020
Country/Territory	Slovakia
City	Bratislava
Period	20/9/14 → 20/9/17

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1A2C2002577).

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-59065-9_1

Cite this

Timakum, T., Lee, S., Song, I. Y., & Song, M. (2020). Analyzing the research landscape of DaWaK papers from 1999 to 2019. In M. Song, I-Y. Song, G. Kotsis, I. Khalil, & A. M. Tjoa (Eds.), Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings (pp. 3-13). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12393 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59065-9_1

Timakum, Tatsawan ; Lee, Soobin ; Song, Il Yeol et al. / Analyzing the research landscape of DaWaK papers from 1999 to 2019. Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings. editor / Min Song ; Il-Yeol Song ; Gabriele Kotsis ; Ismail Khalil ; A Min Tjoa. Springer Science and Business Media Deutschland GmbH, 2020. pp. 3-13 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The International Conference on Big Data Analytics and Knowledge Discovery (DaWaK) has become a key conduit to exchange experience and knowledge among researchers and practitioners in the field of data warehousing and knowledge discovery. This study has quantitatively analyzed the 775 papers published in DaWaK from 1999 to 2019. This study presents the knowledge structure of the DaWaK papers and identifies the evolution of research topics in this discipline. Several text mining techniques were applied to analyze the contents of the research fields and to structure the knowledge presented at DaWaK. Dirichlet Multinomial Regression (DMR) is used to examine the trend of the research topics. Research metrics were used to identify conference and paper performance in terms of citation counts, readers, and the number of downloads. The study shows that DaWaK research outcomes have been receiving consistent attention from the scholarly community in the past 21 years. The 775 papers were cited by 4,339 times, marking the average number of citations of each proceeding as 207 times, and the average number of citations per published paper as six times.",

author = "Tatsawan Timakum and Soobin Lee and Song, {Il Yeol} and Min Song",

note = "Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1A2C2002577). Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 22nd International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2020 ; Conference date: 14-09-2020 Through 17-09-2020",

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Timakum, T, Lee, S, Song, IY & Song, M 2020, Analyzing the research landscape of DaWaK papers from 1999 to 2019. in M Song, I-Y Song, G Kotsis, I Khalil & AM Tjoa (eds), Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12393 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 3-13, 22nd International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2020, Bratislava, Slovakia, 20/9/14. https://doi.org/10.1007/978-3-030-59065-9_1

Analyzing the research landscape of DaWaK papers from 1999 to 2019. / Timakum, Tatsawan; Lee, Soobin; Song, Il Yeol et al.
Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings. ed. / Min Song; Il-Yeol Song; Gabriele Kotsis; Ismail Khalil; A Min Tjoa. Springer Science and Business Media Deutschland GmbH, 2020. p. 3-13 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12393 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N1 - Funding Information: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1A2C2002577). Publisher Copyright: © Springer Nature Switzerland AG 2020.

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Timakum T, Lee S, Song IY, Song M. Analyzing the research landscape of DaWaK papers from 1999 to 2019. In Song M, Song I-Y, Kotsis G, Khalil I, Tjoa AM, editors, Big Data Analytics and Knowledge Discovery - 22nd International Conference, DaWaK 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 3-13. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-59065-9_1

Analyzing the research landscape of DaWaK papers from 1999 to 2019

Abstract

Publication series

Conference

Bibliographical note

All Science Journal Classification (ASJC) codes

Access to Document

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