Semi-supervised and un-supervised clustering: A review and experimental evaluation

K Taha - Information Systems, 2023 - Elsevier
Retrieving, analyzing, and processing large data can be challenging. An effective and
efficient mechanism for overcoming these challenges is to cluster the data into a compact …

[PDF][PDF] 机器学习在地震事件自动检测中的应用综述

罗仁昱, 陈继锋, 尹欣欣 - 地球物理学进展, 2021 - dsjyj.com.cn
摘要很多地震学问题的解决都依赖于地震事件的准确检测, 随着计算机软硬件的快速发展,
机器学习学科发展迅速, 其在地震事件自动检测中的应用在过去几十年被广泛研究 …

Motiflets: Simple and Accurate Detection of Motifs in Time Series

P Schäfer, U Leser - Proceedings of the VLDB Endowment, 2022 - dl.acm.org
A time series motif intuitively is a short time series that repeats itself approximately the same
within a larger time series. Such motifs often represent concealed structures, such as heart …

Faser: Seismic phase identifier for automated monitoring

FA Chowdhury, MA Siddiquee, GE Baker… - Proceedings of the 27th …, 2021 - dl.acm.org
Seismic phase identification classifies the type of seismic wave received at a station based
on the waveform (ie, time series) recorded by a seismometer. Automated phase …

Motiflets--Fast and Accurate Detection of Motifs in Time Series

P Schäfer, U Leser - arXiv preprint arXiv:2206.03735, 2022 - arxiv.org
A motif intuitively is a short time series that repeats itself approximately the same within a
larger time series. Such motifs often represent concealed structures, such as heart beats in …

Domain Specific Feature Representation Learning for Diverse Temporal Data

FA Chowdhury - 2023 - digitalrepository.unm.edu
Humans can leverage domain context to recognize novel patterns and categories based on
limited known examples. In contrast, computational learning methods are not adept at …