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REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition


Klepac, Goran; Kopal, Robert; Mršić, Leo
REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition // Hybrid Soft Computing Approaches / Siddhartha Bhattacharyya, Paramartha Dutta, Susanta Chakraborty (ur.).
India: Springer India, 2016. str. 237-270


Naslov
REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition

Autori
Klepac, Goran ; Kopal, Robert ; Mršić, Leo

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Hybrid Soft Computing Approaches

Urednik/ci
Siddhartha Bhattacharyya, Paramartha Dutta, Susanta Chakraborty

Izdavač
Springer India

Grad
India

Godina
2016

Raspon stranica
237-270

ISBN
978-81-322-2543-0

Ključne riječi
REFII Model

Sažetak
He article will present the methodology for holistic time series analysis, based on time series transformation model REFII (REFII is an acronym for Raise-Equal-Fall and the model version is II or 2) Patel et al. (Mining motifs in massive time series databases, 2002) [1], Perng and Parker (SQL/LPP: a time series extension of SQL based on limited patience patterns, 1999) [2], Popivanov and Miller (Similarity search over time series data using wavelets, 2002) [3]. The main purpose of REFII model is to automate time series analysis through a unique transformation model of time series. The advantage of this approach to a time series analysis is the linkage of different methods for time series analysis linking traditional data mining tools in time series, and constructing new algorithms for analyzing time series. REFII model is not a closed system, which means that there is a finite set of methods. This is primarily a model used for transformation of values of time series, which prepares data used by different sets of methods based on the same model of transformation in the domain of problem space. REFII model gives a new approach in time series analysis based on a unique model of transformation, which is a base for all kind of time series analyses. In combination with elements of other methods, such as self- organizing maps or frequent-pattern trees, REFII models can make new hybrid methods for efficient time temporal data mining. Similar principle of hybridization could be used as a tool for time series temporal pattern recognition. The article describes real case study illustrating practical application of described methodology.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove
Visoko učilište Algebra, Zagreb

Profili:

Avatar Url Goran Klepac (autor)

Avatar Url Leo Mršić (autor)

Avatar Url Robert Kopal (autor)

Citiraj ovu publikaciju

Klepac, Goran; Kopal, Robert; Mršić, Leo
REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition // Hybrid Soft Computing Approaches / Siddhartha Bhattacharyya, Paramartha Dutta, Susanta Chakraborty (ur.).
India: Springer India, 2016. str. 237-270
Klepac, G., Kopal, R. & Mršić, L. (2016) REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition. U: Siddhartha Bhattacharyya, Paramartha Dutta, Susanta Chakraborty (ur.) Hybrid Soft Computing Approaches. India, Springer India, str. 237-270.
@inbook{inbook, year = {2016}, pages = {237-270}, keywords = {REFII Model}, isbn = {978-81-322-2543-0}, title = {REFII Model as a Base for Data Mining Techniques Hybridization with Purpose of Time Series Pattern Recognition}, keyword = {REFII Model}, publisher = {Springer India}, publisherplace = {India} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Book Citation Index - Science (BKCI-S)
  • Scopus