Advancements in Household Data Mining: Fine-Tuning of Usage Pattern Inference Pipeline

Ramona Tolas; Raluca Portase; Rodica Potolea

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Paper

Advancements in Household Data Mining: Fine-Tuning of Usage Pattern Inference Pipeline

Topics: Analytics, Intelligence and Knowledge Engineering; Artificial Intelligence; Big Data Algorithm, Methodology, Business Models and Challenges; Data Processing ; Sensor Networks, Remote Diagnosis and Development; Sensors

In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security IoTBDS - Volume 1, 53-61, 2024 , Angers, France

Authors: Ramona Tolas ; Raluca Portase and Rodica Potolea

Affiliation: Technical University of Cluj-Napoca, Romania

Keyword(s): Usage Mining, Time Series Feature Extraction, Synthetic Household Data Generation, Wavelet Transform, Dimensionality Reduction.

Abstract: In the era of rapidly expanding smart household devices, a surge in data generation within domestic environments has occurred. This paper focuses on optimizing knowledge inference methods from this rich household-generated data, building upon our earlier work for uncovering intricate usage patterns. This work addresses non-functional requirements, emphasizing data processing efficiency by introducing innovative techniques for dimensionality reduction. Another contribution of this research is the formalization of a synthetic data generation process, crucial for comprehensive testing and data privacy compliance. Overall, this work advances household data mining by refining usage pattern inference pipeline, enhancing performance, and providing a framework for synthetic data generation.

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Paper citation in several formats:

Tolas, R.; Portase, R. and Potolea, R. (2024). Advancements in Household Data Mining: Fine-Tuning of Usage Pattern Inference Pipeline. In Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - IoTBDS; ISBN 978-989-758-699-6; ISSN 2184-4976, SciTePress, pages 53-61. DOI: 10.5220/0012598000003705

@conference{iotbds24,
author={Ramona Tolas. and Raluca Portase. and Rodica Potolea.},
title={Advancements in Household Data Mining: Fine-Tuning of Usage Pattern Inference Pipeline},
booktitle={Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - IoTBDS},
year={2024},
pages={53-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012598000003705},
isbn={978-989-758-699-6},
issn={2184-4976},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Internet of Things, Big Data and Security - IoTBDS
TI - Advancements in Household Data Mining: Fine-Tuning of Usage Pattern Inference Pipeline
SN - 978-989-758-699-6
IS - 2184-4976
AU - Tolas, R.
AU - Portase, R.
AU - Potolea, R.
PY - 2024
SP - 53
EP - 61
DO - 10.5220/0012598000003705
PB - SciTePress