A process mining-based error correction approach to improve data quality of an IoT-sourced event log

Autor:	Shirali, Mohsen, Ahmadi, Zahra, Fernández-Llatas, Carlos, Bayo-Monton, Jose-Luis, Di Federico, Gemma
Rok vydání:	2024
Předmět:	Computer Science - Databases Computer Science - Emerging Technologies E.0 H.4.0 J.3 J.0
Druh dokumentu:	Working Paper
DOI:	10.1145/3680289
Popis:	Internet of Things (IoT) systems are vulnerable to data collection errors and these errors can significantly degrade the quality of collected data, impact data analysis and lead to inaccurate or distorted results. This article emphasizes the importance of evaluating data quality and errors before proceeding with analysis and considering the effectiveness of error correction methods for a smart home use case. Comment: 10 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.13091 Zobrazit plný text záznamu View this record from Arxiv