Theoretical Challenges in Knowledge Discovery in Big Data - A Logic Reasoning and a Graph Theoretical Point of View

Pavel Surynek, Petra Surynková

2014

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.

Paper Citation

in Harvard Style

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

in Bibtex Style

@conference{keod14,
author={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},
}

in EndNote Style

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 - Surynková P.
PY - 2014
SP - 327
EP - 332
DO - 10.5220/0005092503270332