Title :
Mining time series data via linguistic summaries of trends by using a modified Sugeno integral based aggregation
Author :
Janusz Kacprzyk;Anna Wilbik;Slawomir Zadrozny
Author_Institution :
Fellow, IEEE, Systems Research Institute, Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw, Poland and Warsaw School of Information Technology (WIT) ul. Newelska 6, 01-447, Warsaw, Poland Email: kacprzyk@ibspan.waw.pl
fDate :
4/1/2007 12:00:00 AM
Abstract :
Linguistic summaries as descriptions of trends in time series data are proposed. We further extend our (cf. Kacprzyk, Wilbik and Zadrozny, 2006) previous works in which we put forward a new approach to the linguistic summarization of time series. In this paper we basically propose a modification of our previous work on the use of the Sugeno integral developed in 2006 by employing a modified fuzzy measure and its related modified Sugeno integral. This gives better results in particular in the case of some more sophisticated and extended types of summaries
Keywords :
"Data mining","Humans","Natural languages","Time series analysis","Calculus","Computational intelligence","Statistical analysis","Neural networks","Bridges","Biology computing"
Conference_Titel :
Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
Print_ISBN :
1-4244-0705-2
DOI :
10.1109/CIDM.2007.368950