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@inproceedings{40287,
author = {Peschel, Jakub and Batko, Michal and Zezula, Pavel},
address = {New York, NY, USA,},
booktitle = {Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems},
doi = {http://dx.doi.org/10.1145/3415048.3416097},
keywords = {Data analysis; Similarity search; Pattern mining},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, NY, USA,},
isbn = {978-1-4503-8769-9},
pages = {1-5},
publisher = {Association for Computing Machinery},
title = {Techniques for Complex Analysis of Contemporary Data},
url = {https://dl.acm.org/doi/10.1145/3415048.3416097},
year = {2020}
}
TY - JOUR
ID - 40287
AU - Peschel, Jakub - Batko, Michal - Zezula, Pavel
PY - 2020
TI - Techniques for Complex Analysis of Contemporary Data
PB - Association for Computing Machinery
CY - New York, NY, USA,
SN - 9781450387699
KW - Data analysis
KW - Similarity search
KW - Pattern mining
UR - https://dl.acm.org/doi/10.1145/3415048.3416097
N2 - Contemporary data objects are typically complex, semi-structured, or unstructured at all. Besides, objects are also related to form a network. In such a situation, data analysis requires not only the traditional attribute-based access but also access based on similarity as well as data mining operations. Though tools for such operations do exist, they usually specialise in operation and are available for specialized data structures supported by specific computer system environments. In contrary, advance analyses are obtained by application of several elementary access operations which in turn requires expert knowledge in multiple areas. In this paper, we propose a unification platform for various data analytical operators specified as a general-purpose analytical system ADAMiSS. An extensible data-mining and similarity-based set of operators over a common versatile data structure allow the recursive application of heterogeneous operations, thus allowing the definition of complex analytical processes, necessary to solve the contemporary analytical tasks. As a proof-of-concept, we present results that were obtained by our prototype implementation on two real-world data collections: the Twitter Higg's boson and the Kosarak datasets.
ER -
PESCHEL, Jakub, Michal BATKO a Pavel ZEZULA. Techniques for Complex Analysis of Contemporary Data. Online. In \textit{Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems}. New York, NY, USA,: Association for Computing Machinery, 2020, s.~1-5. ISBN~978-1-4503-8769-9. Dostupné z: https://dx.doi.org/10.1145/3415048.3416097.
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