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A split-merge evolutionary clustering algorithm
Technical University Sofia Branch Plovdiv, BUL.
Sirris, Brussels, BEL.
2019 (engelsk)Inngår i: ICAART 2019 - Proceedings of the 11th International Conference on Agents and Artificial Intelligence, SciTePress , 2019, Vol. 2, s. 337-346Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

In this article we propose a bipartite correlation clustering technique that can be used to adapt the existing clustering solution to a clustering of newly collected data elements. The proposed technique is supposed to provide the flexibility to compute clusters on a new portion of data collected over a defined time period and to update the existing clustering solution by the computed new one. Such an updating clustering should better reflect the current characteristics of the data by being able to examine clusters occurring in the considered time period and eventually capture interesting trends in the area. For example, some clusters will be updated by merging with ones from newly constructed clustering while others will be transformed by splitting their elements among several new clusters. The proposed clustering algorithm, entitled Split-Merge Evolutionary Clustering, is evaluated and compared to another bipartite correlation clustering technique (PivotBiCluster) on two different case studies: expertise retrieval and patient profiling in healthcare. Copyright © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved

sted, utgiver, år, opplag, sider
SciTePress , 2019. Vol. 2, s. 337-346
Emneord [en]
Bipartite Clustering, Data Mining, Evolutionary Clustering, PubMed Data, Unsupervised Learning, Artificial intelligence, Cluster analysis, Evolutionary algorithms, Bipartite correlation clustering, Case-studies, Clustering solutions, Current characteristic, Data elements, Clustering algorithms
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Identifikatorer
URN: urn:nbn:se:bth-17896Scopus ID: 2-s2.0-85064827857ISBN: 9789897583506 (tryckt)OAI: oai:DiVA.org:bth-17896DiVA, id: diva2:1316776
Konferanse
11th International Conference on Agents and Artificial Intelligence, ICAART; Prague, 19 February 2019 through 21 February 2019
Tilgjengelig fra: 2019-05-21 Laget: 2019-05-21 Sist oppdatert: 2019-05-21bibliografisk kontrollert

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  • en-GB
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