Techniques for Complex Analysis of Contemporary Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00114809" target="_blank" >RIV/00216224:14330/20:00114809 - isvavai.cz</a>
Result on the web
<a href="https://dl.acm.org/doi/10.1145/3415048.3416097" target="_blank" >https://dl.acm.org/doi/10.1145/3415048.3416097</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3415048.3416097" target="_blank" >10.1145/3415048.3416097</a>
Alternative languages
Result language
angličtina
Original language name
Techniques for Complex Analysis of Contemporary Data
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/VI20172020096" target="_blank" >VI20172020096: Complex Analysis and Visualization of Large-scale Heterogeneous Data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems
ISBN
9781450387699
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
1-5
Publisher name
Association for Computing Machinery
Place of publication
New York, NY, USA,
Event location
Athens, Greece
Event date
Jan 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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