Proceedings of the 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering

Publication: ResearchAnthology

  • Ira Assent (Editor)
  • Carlotta Domeniconi
    Carlotta DomeniconiGeorge Mason UniversityUnited States
  • Francesco Gullo
    Francesco GulloYahoo! ResearchSpain
  • Andrea Tagarelli
    Andrea Tagarelli University of CalabriaItaly
  • Arthur Zimek
    Arthur Zimek Ludwig-Maximilians-Universität MünchenGermany
Cluster detection is a very traditional data analysis task with several decades of research. However, it also includes a large variety of different subtopics investigated by different communities such as data mining, machine learning, statistics, and database systems. "Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering" names several challenges around clustering: making sense or even making use of many, possibly redundant clustering results, of different representations and properties of data, of different sources of knowledge. Approaches such as ensemble clustering, semi-supervised clustering, subspace clustering meet around these problems. Yet they tackle these problems with different backgrounds, focus on different details, and include ideas from different research communities. This diversity is a major potential for this emerging field and should be highlighted by this workshop. A core motivation for this workshop series is our believe that these approaches are not just tackling different parts of the problem but that they should benefit from each other and, ultimately, combine the different perspectives and techniques to tackle the clustering problem more effectively. In paper presentations and discussions, we therefore would like to encourage the workshop participants to look at their own research problems from multiple perspectives.
Original languageEnglish
PublisherAssociation for Computing Machinery
Number of pages37
ISBN (print)978-1-4503-2334-5
StatePublished - 2013
Event - Chicago, United States


WorkshopMultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering
CountryUnited States

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