Ant-Based Clustering in Delta Episode Information Systems Based on Temporal Rough Set Flow Graphs

• Autorzy: Pancerz, K. , Lewicki, A. , Tadeusiewicz, R. , Warchoł, J.
• Języki publikacji: EN

Abstrakty

EN

In the paper, we focus on ant-based clustering time series data represented by means of the so-called delta episode information systems. A clustering process is made on the basis of delta representation of time series, i.e., we are interested in characters of changes between two consecutive data points in time series instead of original data points. Most algorithms use similarity measures to compare time series. In the paper, we propose to use a measure based on temporal rough set flow graphs. This measure has a probabilistic character and it is considered in terms of the Decision Theoretic Rough Set (DTRS) model. To perform ant-based clustering, the algorithm based on the versions proposed by J. Deneubourg, E. Lumer and B. Faieta as well as J. Handl et al. is used.

Słowa kluczowe

EN

information storage; retrieval systems; rough sets; flow graphs; graph theory; time series analysis; computer algorithms

• Czasopismo: Fundamenta Informaticae
• Rocznik: 2013
• Tom: Vol. 128, nr 1-2
• Strony: 143--158
• Opis fizyczny: Bibliogr. 30 poz., rys., tab.

Twórcy

autor

Pancerz, K.

• University of Management and Administration, Akademicka Str. 4, 22-400 Zamość, Poland,

autor

Lewicki, A.

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

autor

Tadeusiewicz, R.

• AGH University of Science and Technology, Mickiewicza Av. 30, 30-059 Kraków, Poland,

autor

Warchoł, J.

• Medical University of Lublin, Jaczewskiego Str. 4, 20-090 Lublin, Poland,

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