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Authors: Pavel Surynek 1 and Petra Surynková 2

Affiliations: 1 Charles University Prague, Czech Republic ; 2 Charles University in Prague, Czech Republic

ISBN: 978-989-758-049-9

Keyword(s): Big Data, Data Analysis, Logic Reasoning, Graph Theory, Graph Drawing, Propositional Satisfiability.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Domain Analysis and Modeling ; Enterprise Software Technologies ; Intelligent Problem Solving ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Software Engineering ; Symbolic Systems

Abstract: This paper addresses a problem of knowledge discovery in big data from the point of view of theoretical computer science. Contemporary characterization of big data is often preoccupied by its volume, velocity of change, and variety that causes technical difficulties to handle the data efficiently while theoretical challenges that are offered by big data are neglected at the same time. Contrary to this preoccupation with technical issues, we would like to discuss more theoretical issues focused on the goal briefly expressed as what be understood from big data by imitating human like reasoning through logic and algorithmic means. The ultimate goal marked out in this paper is to develop an automation of the reasoning process that can manipulate and understand data in volumes that is beyond human abilities and to investigate if substantially different patterns appear in big data than in small data.

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Paper citation in several formats:
Surynek, P.; Surynek, P. and Surynková, P. (2014). Theoretical Challenges in Knowledge Discovery in Big Data - A Logic Reasoning and a Graph Theoretical Point of View.In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014) ISBN 978-989-758-049-9, pages 327-332. DOI: 10.5220/0005092503270332

@conference{keod14,
author={Pavel Surynek. and Pavel Surynek. and Petra Surynková.},
title={Theoretical Challenges in Knowledge Discovery in Big Data - A Logic Reasoning and a Graph Theoretical Point of View},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)},
year={2014},
pages={327-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005092503270332},
isbn={978-989-758-049-9},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)
TI - Theoretical Challenges in Knowledge Discovery in Big Data - A Logic Reasoning and a Graph Theoretical Point of View
SN - 978-989-758-049-9
AU - Surynek, P.
AU - Surynek, P.
AU - Surynková, P.
PY - 2014
SP - 327
EP - 332
DO - 10.5220/0005092503270332

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