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Extracting Knowledge from Stream Behavioural Patterns

Topics: Big Data Algorithm, Methodology, Business Models and Challenges; Context-awareness and Location-awareness ; Data Analysis and Visualization for Smart City, Green Systems and Transport Systems; Data and Knowledge Management ; Data Management for Large Data; Data Processing ; Future of IoT and Big Data; Intelligent Systems for IoT and Services Computing ; Internet of Things; Large-scale Information Systems and Applications; Machine to Machine Communications ; Modeling, Experiments, Sharing Technologies & Platforms; Performance Evaluation and Modeling ; Software Architecture and Middleware

Authors: Ricardo Jesus ; Mário Antunes ; Diogo Gomes and Rui Aguiar

Affiliation: Universidade de Aveiro, Portugal

ISBN: 978-989-758-245-5

Keyword(s): Stream Mining, Machine Learning, IoT, M2M, Context Awareness.

Related Ontology Subjects/Areas/Topics: Data Communication Networking ; Enterprise Information Systems ; Internet of Things ; Sensor Networks ; Software Agents and Internet Computing ; Software and Architectures ; Telecommunications

Abstract: The increasing number of small, cheap devices full of sensing capabilities lead to an untapped source of information that can be explored to improve and optimize several systems. Yet, as this number grows it becomes increasingly difficult to manage and organize all this new information. The lack of a standard context representation scheme is one of the main difficulties in this research area (Antunes et al., 2016b). With this in mind we propose a stream characterization model which aims to provide the foundations of a new stream similarity metric. Complementing previous work on context organization, we aim to provide an automatic organizational model without enforcing specific representations.

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Paper citation in several formats:
Jesus R., Antunes M., Gomes D. and Aguiar R. (2017). Extracting Knowledge from Stream Behavioural Patterns.In Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-245-5, pages 419-423. DOI: 10.5220/0006373804190423

@conference{iotbds17,
author={Ricardo Jesus and Mário Antunes and Diogo Gomes and Rui Aguiar},
title={Extracting Knowledge from Stream Behavioural Patterns},
booktitle={Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2017},
pages={419-423},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006373804190423},
isbn={978-989-758-245-5},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Extracting Knowledge from Stream Behavioural Patterns
SN - 978-989-758-245-5
AU - Jesus R.
AU - Antunes M.
AU - Gomes D.
AU - Aguiar R.
PY - 2017
SP - 419
EP - 423
DO - 10.5220/0006373804190423

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