TY  - GEN
N2  - The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.
DO  - 10.1007/978-3-030-59065-9
DO  - doi
AB  - The volume LNCS 12393 constitutes the papers of the 22nd International Conference Big Data Analytics and Knowledge Discovery which will be held online in September 2020. The 15 full papers presented together with 14 short papers plus 1 position paper in this volume were carefully reviewed and selected from a total of 77 submissions. This volume offers a wide range to following subjects on theoretical and practical aspects of big data analytics and knowledge discovery as a new generation of big data repository, data pre-processing, data mining, text mining, sequences, graph mining, and parallel processing.
T1  - Big data analytics and knowledge discovery :22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings /
AU  - Song, Min
AU  - Song, Il-Yeol.
AU  - Kotsis, Gabriele,
AU  - Tjoa, A Min.
AU  - Khalil, Ismail,
VL  - v.12393
CN  - QA76.9.D3
ID  - 944850
KW  - Big data
KW  - Data mining
KW  - Database management.
KW  - Application software.
KW  - Education
KW  - Computer architecture.
KW  - Information organization.
KW  - Information storage and retrieval systems.
SN  - 9783030590659
SN  - 3030590658
TI  - Big data analytics and knowledge discovery :22nd International Conference, DaWaK 2020, Bratislava, Slovakia, September 14-17, 2020, Proceedings /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-59065-9
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-59065-9
ER  -