TIME SERIES DATA MINING

By Nuno Filipe Castro. 2010

495 citations recorded by the source corpus.

Subfields: Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/544cfb22b8322c03bcc0ba56d86bb8996cd55e95

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. José Antonio Lozano
2. Geoffrey I. Webb
3. Athanasios V. Vasilakos
4. Cesare Alippi
5. Shirui Pan
6. Jiafu Wan
7. S. Kotsiantis
8. Raymond J. Mooney

In Signal Processing

1. José Antonio Lozano
2. Geoffrey I. Webb
3. Athanasios V. Vasilakos
4. Cesare Alippi
5. Ane Blázquez-García
6. Shirui Pan
7. Qingsong Wen
8. Usue Mori

Citations in the corpus

• A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection (2023, background): “T HE advent of advanced sensing and data stream processing technologies has led to an explosion of time series data [1], [2], [3].”
• A Review on Outlier/Anomaly Detection in Time Series Data (2020, background): “Alternatively, Galeano et al. [2006] suggest reducing the dimensionality with projection pursuit, which aims to find the best projections to identify outliers.”
• Data Mining for the Internet of Things: Literature Review and Challenges (2015, background): “Commonly, time series task relies on 3 parts of components, including representation, similarity measures, and indexing (see Figure 5) [82, 83].”