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 …

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 …

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 …

Trajectory similarity computation is fundamental functionality with many applications such as
animal migration pattern studies and vehicle trajectory mining to identify popular routes and …

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 …

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 …

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 …

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 …

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 …

Trajectory analytics can benefit many real-world applications, eg, frequent trajectory based
navigation systems, road planning, car pooling, and transportation optimizations. Existing …