To the best of our knowledge, this work constitutes the first attempt on continuous medoid queries. First, we consider centralized monitoring, where the points ...

We demonstrate the efficiency and efficacy of our techniques through extensive experiments. Keywords: Medoid Queries, Continuous Query Processing, Moving Object.

This work addresses centralized monitoring and distributed monitoring of the k-medoid problem, where the points issue location updates whenever they move, ...

The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and ...

The server collects these locations and continuously updates the results of registered spatial queries. Our work fo- cuses on continuous k-means monitoring over ...

Filters of a spatial nature have been employed in the literature on continuous monitoring of range [36,11,80], nearest neighbor [48,92] and medoid [77] queries.

clustering moving objects based on a spatial network. Here, the distance between the objects is defined by their shortest path distance over the network.

In this paper, we focus on data containing attribute-level uncertainty, which is modeled according to a probabilistic model. We hereinafter refer to this data.

Open access academic research from top universities on the subject of Databases and Information Systems.

The objective of cluster analysis is to partition a set of objects into two or more clusters such that objects within a cluster are similar and objects in ...