Das, "Time Series Similarity Measures," Tutorial Notes Sixth Int'l Conf. Knowledge Discovery and Data Mining, pp. 243-307, 2000.D. Gunopulos,G Das.Time series similarity measures.Tutorial notes of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining. 2000...
With high precision, DTW is one of the most prevalent similarity measures for time series [1], [4], [7], [17]. However, the computational complexity of DTW is O(n2), which greatly limits its application to the high dimensional time series and the dynamic data stream. Many methods have...
es and reduce the calculating complexity.Experimentally compares the four similarity measures on three database under group-ward hierarchical clustering,evaluates the results objectively and subjecttively respectively,and is shown to yield useful and reasonable clustering,especially for economic time series....
Traditional techniques for measuring similarities between time series are based on handcrafted similarity measures, whereas more recent learning-based approaches cannot exploit external supervision. We combine ideas from time-series modeling and metric learning, and study siamese recurrent networks (SRNs) th...
1.An efficient lower bounding technique is proposed based on Dynamic Time Warping(DTW) for time series similarity search,which measures the distance between original sequence reduced dimensionality by Piecewise Aggregate Approximation(PAA) approximation method and query sequence reduced dimensionality by Grid...
Time series similarity computation is a fundamental primitive that underpins many time series data analysis tasks. However, many existing time series similarity measures have a high computation cost. While there has been much research effort for reducing the computational cost, such effort is usually ...
Multivariate time series (MTS) datasets are very common in various financial, multimedia, and hydrological fields. In this paper, a dimension-combination method is proposed to search similar sequences for MTS. Firstly, the similarity of single-dimension series is calculated; then the overall similari...
Related events are found using time series similarity measures between events and abnormal stat metrics. After training deep autoencoder with DBMS metric data, efficacy of anomaly detection is investigated from other DBMSs containing anomalies. Experiment results show effectiveness of proposed model, ...
Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining The chapter is organized as follows. Section 2 will introduce the similarity matchingproblem on time series. We will note the importance of the use of efficient data structures toperform search, and the choice of...
The Influence of Global Constraints on DTW and LCS Similarity Measures for Time-Series Databases Analysis of time series represents an important tool in many application areas. A vital component in many types of time-series analysis is the choice of an... V Kurbalija,Radovanovi, Milo,Z Geler...