Searching for similar trajectories from a database is an important way for extracting human-
understandable knowledge. However, due to the huge volume of trajectories and high …

Abstract The Vapnik–Chervonenkis dimension provides a notion of complexity for systems of
sets. If the VC dimension is small, then knowing this can drastically simplify fundamental …

The Fr\'echet distance provides a natural and intuitive measure for the popular task of
computing the similarity of two (polygonal) curves. While a simple algorithm computes it in …

Mining time series motifs is a fundamental, yet expensive task in exploratory data analytics.
In this paper, we therefore propose a fast method to find the top-k motifs with probabilistic …

Similarity joins are recognized to be among the most used data processing and analysis
operations. We introduce a C++-based high-level parallel pattern implemented on top of …

Massive datasets of spatial trajectories representing the mobility of a diversity of moving
objects are ubiquitous in research and industry. Similarity search of a large collection of …

Similarity joins are recognized to be among the most useful data processing and analysis
operations. A similarity join is used to retrieve all data pairs whose distances are smaller …

Consider the natural question of how to measure the similarity of curves in the plane by a
quantity that is invariant under translations of the curves. Such a measure is justified …

Advances in wireless communication technology have allowed for the collection of large-
scale human motion trajectories by recording the appearance of mobile devices within the …

The Fréchet distance is a popular distance measure for curves which naturally lends itself to
fundamental computational tasks, such as clustering, nearest-neighbor searching, and …