Computing trajectory similarity is a fundamental operation in movement analytics, required
in search, clustering, and classification of trajectories, for example. Yet the range of different …

Center-based clustering, in particular k-means clustering, is frequently used for point data.
Its advantages include that the resulting clustering is often easy to interpret and that the …

We study the c-approximate near neighbor problem under the continuous Fréchet distance:
Given a set of n polygonal curves with m vertices, a radius δ> 0, and a parameter k≤ m, we …

The increasingly large volume of trajectories of moving entities obtained through GPS and
cellphone tracking, telemetry, and other location‐aware technologies motivates researchers …

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 …

In the realm of autonomous driving, ensuring a secure halt is imperative across diverse
scenarios, ranging from routine stops at traffic lights to critical situations involving detected …

We study the problem of sub-trajectory nearest-neighbor queries on polygonal curves under
the continuous Fréchet distance. Given an n vertex trajectory P and an m vertex query …

激光钻进岩石形成的钻孔的孔形较为复杂, 具有较小的孔直径和较高的孔壁粗糙度,
使得利用传统方法进行钻孔尺寸的测量较为困难. 为了精确钻孔测量和方便孔形研究 …

We study the $ k $-median clustering problem for high-dimensional polygonal curves with
finite but unbounded number of vertices. We tackle the computational issue that arises from …

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 …