Online data clustering algorithms in an RTLS system

Online data clustering algorithms in an RTLS system

This paper proposes and evaluates solutions for an online clustering problem and gives a mathematical model for it. The problem at hand occurs often in the fusion of data streams for example in real time locating systems. The goal is to gather as much incoming information from several sources as possible but also minimize the delay before the next processing step can be executed. The key charac...

Online Clustering Algorithms

We introduce a set of clustering algorithms whose performance function is such that the algorithms overcome one of the weaknesses of K-means, its sensitivity to initial conditions which leads it to converge to a local optimum rather than the global optimum. We derive online learning algorithms and illustrate their convergence to optimal solutions which K-means fails to find. We then extend the ...

A Comparative Study of Some Clustering Algorithms on Shape Data

Recently, some statistical studies have been done using the shape data. One of these studies is clustering shape data, which is the main topic of this paper. We are going to study some clustering algorithms on shape data and then introduce the best algorithm based on accuracy, speed, and scalability criteria. In addition, we propose a method for representing the shape data that facilitates and ...

Online algorithms for clustering problems

Three-Tier Clustering: An Online Citation Clustering System

In this paper, we present an online citation entry clustering system based on three-tier clustering. The objective is to further process search results returned by bibliography databases and present to the user with more accurate results. By our approach, a user first issues an author name query and it is passed to a data source chosen by the user. We then exploit the unique usage of each citat...