Authors:
Man Tianxing
1
;
Nataly Zhukova
2
;
Nguyen Than
1
;
Alexander Nechaev
3
and
Sergey Lebedev
4
Affiliations:
1
ITMO University, St. Petersburg and Russia
;
2
ITMO University, St. Petersburg, Russia, St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg and Russia
;
3
Vyatka State University, Kirov and Russia
;
4
Saint-Petersburg Electrotechnical University, St. Petersburg and Russia
Keyword(s):
Data Processing, Machine Learning, Multilayer Structure, Algorithm Selection, Ontology.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Informatics in Control, Automation and Robotics
;
Information-Based Models for Control
;
Intelligent Control Systems and Optimization
;
Knowledge-Based Systems Applications
;
Machine Learning in Control Applications
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Currently, data processing technology is applied in various fields. But non-expert researchers are always confused about its diversity and complex processes. Especially due to the instability of real data, the preparation process for extracting information is lengthy. At the same time, different analysis algorithms are based on different mathematical models, so they are suitable for different situations. In the real data processing process, inappropriate data forms and algorithm selections always lead to unsatisfactory results. This paper proposes a multilayer description model of data processing algorithms and implements it based on ontology technology. The model provides a multi-layered structure including data pre-processing, data form conversion, and output model selection so that the user can obtain a complete data processing process from it. The extensibility and interpretability of ontology also provide a huge space for model improvement. The multilevel structure greatly reduc
es its complexity.
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