A Representative Set Method for Symbolic Sequence Clustering

• Autorzy: Kozarzewski, B.
• Języki publikacji: EN

Abstrakty

EN

Sequence decomposition into a set of consecutive, distinct subsequences is crucial for symbolic sequence analysis. It reduces significantly the reference base of the recorded sequence for further retrieval and allows for original similarity and membership measures of the sequences. The introduced measures are a start point to a new algorithm for clustering sequences into groups of similar individuals. Algorithms that use the concept of a representative set achieved relatively good clustering results. The representative set that we have introduced is precisely and uniquely defined in contrast to that used in other applications.

Słowa kluczowe

EN

similarity and membership measures; representative set; clustering

• Czasopismo: Computational Methods in Science and Technology
• Rocznik: 2013
• Tom: Vol. 19, No. 2
• Strony: 99--105
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Kozarzewski, B.

• University of Information Technology and Management ul. H. Sucharskiego 2, 35-225 Rzeszów, Poland,

Bibliografia

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