Abstract This article summarizes and evaluates the clustering effects of commonly used algorithms on data sets with different density distributions. In this paper, circled datasets, sized Gaussian mixture datasets were designed as typical datasets. Then, K-means, clustering, DBSCAN, Agglomerative developed to evaluate performance these The results show that DBSCAN is more stable when distributi...

Today world's dependence on the Internet and the emerging of Web 2.0 applications is significantly increasing the requirement of web robots crawling the sites to support services and technologies. Regardless of the advantages of robots, they may occupy the bandwidth and reduce the performance of web servers. Despite a variety of researches, there is no accurate method for classifying huge data ...

Knowledge extraction from data streams has received increasing interest in recent years. However, most of the existing studies assume that the class distribution of data streams is relatively balanced. The reaction of concept drifts is more difficult if a data stream is class imbalanced. Current oversampling methods generally selectively absorb the previously received minority examples into the...

We developed a program that automatically creates a crowd sourced tourist guide for a selected city. This tourist guide is to be based on the data of Flickr. To do this, the program analyses the meta data of geotagged photos from the image hosting platform Flickr. These geotagged photos are clustered using DBSCAN to find the places with the highest density of photos. These high density places s...

This paper presents EDACluster, an Estimation of Distribution Algorithm (EDA) applied to the clustering task. EDA is an Evolutionary Algorithm used here to optimize the search for adequate clusters when very little is known about the target dataset. The proposed algorithm uses a mixed approach – density and grid-based – to identify sets of dense cells in the dataset. The output is a list of ite...

Biometrische Verfahren werden häufig im Rahmen der Authentifizierung zum Schutz wichtiger Daten und Systeme eingesetzt. Hierzu werden biometrische Referenzen gespeichert, die Informationen über biometrische Charakteristika der betroffenen Individuen enthalten. Um diese biometrischen Referenzen in offenen und verteilten biometrischen Systemen nutzen zu können, ist eine Standardisierung der Daten...

Several application domains such as molecular biology and geography produce a tremendous amount of data which can no longer be managed without the help of efficient and effective data mining methods. One of the primary data mining tasks is clustering. However, traditional clustering algorithms often fail to detect meaningful clusters because most real-world data sets are characterized by a high...