Time-series clustering–a decade review
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …
about classes. With emerging new concepts like cloud computing and big data and their vast …
Time-series data mining
P Esling, C Agon - ACM Computing Surveys (CSUR), 2012 - dl.acm.org
In almost every scientific field, measurements are performed over time. These observations
lead to a collection of organized data called time series. The purpose of time-series data …
lead to a collection of organized data called time series. The purpose of time-series data …
k-shape: Efficient and accurate clustering of time series
J Paparrizos, L Gravano - Proceedings of the 2015 ACM SIGMOD …, 2015 - dl.acm.org
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Deep representation learning for trajectory similarity computation
Trajectory similarity computation is fundamental functionality with many applications such as
animal migration pattern studies and vehicle trajectory mining to identify popular routes and …
animal migration pattern studies and vehicle trajectory mining to identify popular routes and …
A survey of trajectory distance measures and performance evaluation
The proliferation of trajectory data in various application domains has inspired tremendous
research efforts to analyze large-scale trajectory data from a variety of aspects. A …
research efforts to analyze large-scale trajectory data from a variety of aspects. A …
A survey on trajectory data management, analytics, and learning
Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …
in the availability and collection of urban trajectory data, thus increasing the demand for …
Experimental comparison of representation methods and distance measures for time series data
The previous decade has brought a remarkable increase of the interest in applications that
deal with querying and mining of time series data. Many of the research efforts in this context …
deal with querying and mining of time series data. Many of the research efforts in this context …
Querying and mining of time series data: experimental comparison of representations and distance measures
The last decade has witnessed a tremendous growths of interests in applications that deal
with querying and mining of time series data. Numerous representation methods for …
with querying and mining of time series data. Numerous representation methods for …
Fast and accurate time-series clustering
J Paparrizos, L Gravano - ACM Transactions on Database Systems …, 2017 - dl.acm.org
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Vehicle trajectory similarity: Models, methods, and applications
The increasing availability of vehicular trajectory data is at the core of smart mobility
solutions. Such data offer us unprecedented information for the development of trajectory …
solutions. Such data offer us unprecedented information for the development of trajectory …