Results 61 to 70 of about 751,199 (239)

HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks

, 2020
The unsupervised detection of anomalies in time series data has important applications in user behavioral modeling, fraud detection, and cybersecurity. Anomaly detection has, in fact, been extensively studied in categorical sequences.
Casiraghi, Giona, Eliassi-Rad, Tina, LaRock, Timothy, Nanumyan, Vahan, Scholtes, Ingo, Schweitzer, Frank   +5 more
core   +1 more source

Identifying Major Hydrologic Change Drivers in a Transboundary Highly Managed Endorheic Basin: Integrating Hydro-ecological Models and Time Series Data Mining Techniques [PDF]

, 2021
Juan S. Acero Triana, Hoori Ajami
openalex   +1 more source

From Code to Concept: A Semantic Approach to AI Innovation Discovery in Open Source Software Repositories

IEEE Access
Artificial Intelligence (AI) is a transformative force driving innovation, yet tracking AI-related advancements remains challenging due to the rapid pace of development and unstructured data from platforms like GitHub.
Inna Novalija, Dumitru Roman, Federico Belotti, Vladimir Alexiev, Luis Rei, Roberto Avogadro, Babak Khalilvandian, Boyan Bechev, Catalina Alexandra Chinie, Iulia Ciurea, Janez Brank, Cosmin Udroiu, Ahmet Soylu, Matteo Palmonari   +13 more
doaj   +1 more source

Time-Series Embedded Feature Selection Using Deep Learning: Data Mining Electronic Health Records for Novel Biomarkers [PDF]

, 2022
Gavin Tsang
openalex   +1 more source

All-chain Sets Mining Algorithm for Multi-scale Nearest Time Series [PDF]

Jisuanji kexue
Mining all-chain set in the time series is an emerging area.To the best of our knowledge,no method has been proposed to mining all-chain sets over multi-scale nearest time series.In this paper,the problem of mining all-chain sets over multi-scale nearest
WANG Shaopeng, FENG Chunkai
doaj   +1 more source

Power Transformer Failure Prediction: Classification in Imbalanced Time Series

U.Porto Journal of Engineering, 2017
This paper describes a study on applying data mining techniques to power transformer failure prediction. The data set used consisted not only on DGA tests, but also in other tests done to the transformer’s insulating oil.
Eduardo e Oliveira, Vera L. Miguéis, Luís Guimarães, José Borges   +3 more
doaj   +1 more source

Modelling Stabilometric Time Series [PDF]

, 2010
Stabilometry is a branch of medicine that studies balance-related human functions. Stabilometric systems generate time series. The analysis of these time series using data mining techniques can be very useful for domain experts.
Caraça-Valente Hernández, Juan Pedro, Lara Torralbo, Juan Alfonso, López-Illescas, África, Pérez Pérez, Aurora   +3 more
core   +1 more source

KV-match: A Subsequence Matching Approach Supporting Normalization and Time Warping [Extended Version]

, 2018
The volume of time series data has exploded due to the popularity of new applications, such as data center management and IoT. Subsequence matching is a fundamental task in mining time series data. All index-based approaches only consider raw subsequence
Pan, Ningting, Wang, Chen, Wang, Jianmin, Wang, Peng, Wang, Wei, Wu, Jiaye   +5 more
core   +1 more source

A literature survey of shapelet quality measures for time series classification [PDF]

PeerJ Computer Science
With the rapid development of the Internet of Things, time series classification (TSC) has gained significant attention from researchers due to its applications in various real-world fields, including electroencephalogram/electrocardiogram classification,
Teng Li, Xiaodong Guo, Cun Ji
doaj   +2 more sources

Understanding Open Source Software Evolution Using Fuzzy Data Mining Algorithm for Time Series Data

Advances in Fuzzy Systems, 2016
Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects.
Munish Saini, Sandeep Mehmi, Kuljit Kaur Chahal   +2 more
doaj   +1 more source