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 Bibliografske baze podataka

Pregled bibliografske jedinice broj: 970658

Časopis

Autori: Lukić, Ivica; Hocenski, Željko; Köhler, Mirko; Galba, Tomislav
Naslov: Parallel mining of uncertain data using segmentation of data set area and Voronoi diagrams
Izvornik: Automatika : časopis za automatiku, mjerenje, elektroniku, računarstvo i komunikacije (0005-1144) 59 (2018), 3-4; 349-356
Vrsta rada: članak
Ključne riječi: Clustering algorithms ; data mining ; data uncertainty ; Euclidean distance ; parallel algorithms
Sažetak:
Clustering of uncertain objects in large uncertain databases and problem of mining uncertain data has been well studied. In this paper, clustering of uncertain objects with location uncertainty is studied. Moving objects, like mobile devices, report their locations periodically, thus their locations are uncertain and best described by a probability density function. The number of objects in a database can be large which makes the process of mining accurate data, a challenging and time consuming task. Authors will give an overview of existing clustering methods and present a new approach for data mining and parallel computing of clustering problems. All existing methods use pruning to avoid expected distance calculations. It is required to calculate the expected distance numerical integration, which is time- consuming. Therefore, a new method, called Segmentation of Data Set Area- Parallel, is proposed. In this method, a data set area is divided into many small segments. Only clusters and objects in that segment are observed. The number of segments is calculated using the number and location of clusters. The use of segments gives the possibility of parallel computing, because segments are mutually independent. Thus, each segment can be computed on multiple cores.
Izvorni jezik: ENG
Rad je indeksiran u
bazama podataka:
Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Kategorija: Znanstveni
URL Internet adrese: https://www.tandfonline.com/doi/full/10.1080/00051144.2018.1541645
Broj citata:
Altmetric:
DOI: 10.1080/00051144.2018.1541645
URL cjelovitog teksta:
Google Scholar: Parallel mining of uncertain data using segmentation of data set area and Voronoi diagrams
Upisao u CROSBI: Ivica Lukić (ivica.lukic@etfos.hr), 26. Stu. 2018. u 13:21 sati



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