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Bipartite Split-Merge Evolutionary Clustering
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.ORCID iD: 0000-0003-3128-191x
Technical University of Sofia, BUL.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
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2019 (English)In: Lect. Notes Comput. Sci., Springer , 2019, p. 204-223Conference paper, Published paper (Refereed)
Abstract [en]

We propose a split-merge framework for evolutionary clustering. The proposed clustering technique, entitled Split-Merge Evolutionary Clustering is supposed to be more robust to concept drift scenarios by providing the flexibility to consider at each step a portion of the data and derive clusters from it to be used subsequently to update the existing clustering solution. The proposed framework is built around the idea to model two clustering solutions as a bipartite graph, which guides the update of the existing clustering solution by merging some clusters with ones from the newly constructed clustering while others are transformed by splitting their elements among several new clusters. We have evaluated and compared the discussed evolutionary clustering technique with two other state of the art algorithms: a bipartite correlation clustering (PivotBiCluster) and an incremental evolving clustering (Dynamic split-and-merge). © Springer Nature Switzerland AG 2019.

Place, publisher, year, edition, pages
Springer , 2019. p. 204-223
Keywords [en]
Bipartite clustering, Data mining, Dynamic clustering, Evolutionary clustering, Split-merge framework, Unsupervised learning, Artificial intelligence, Bipartite correlation clustering, Clustering solutions, Clustering techniques, State-of-the-art algorithms, Cluster analysis
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-19127DOI: 10.1007/978-3-030-37494-5_11Scopus ID: 2-s2.0-85077496461ISBN: 9783030374938 (print)OAI: oai:DiVA.org:bth-19127DiVA, id: diva2:1387915
Conference
11th International Conference on Agents and Artificial Intelligence, ICAART; Prague; Czech Republic; 19 February 2019 through 21 February
Available from: 2020-01-23 Created: 2020-01-23 Last updated: 2020-01-23Bibliographically approved

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Boeva, VeselkaVishnu Manasa, Devagiri

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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Output format
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