TY - CONF
T1 - Linguistic Summarization of Time Series by Using the Choquet Integral
AU - Kacprzyk, Janusz
AU - Wilbik, Anna
AU - Zadrozny, Slawomir
N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2007
Y1 - 2007
N2 - We further extend a new approach to a linguistic summarization of time series proposed in our previous works (cf. Kacprzyk, wilbik and zadrożny [1,2,3,4,5]) in which we put forward the use of a fuzzy linguistic quantifier driven aggregation of trends (partial scores) via the traditional zadeh calculus of linguistically quantified propositions and the sugeno integral. Here we use for this purpose the choquet integral that has been widely advocated for many decision analytic and economic problems. The results are intuitively appealing and the method is effective and efficient.keywordslinguistic termmean absolute deviationfuzzy measurelinguistic labelpartial scorethese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
AB - We further extend a new approach to a linguistic summarization of time series proposed in our previous works (cf. Kacprzyk, wilbik and zadrożny [1,2,3,4,5]) in which we put forward the use of a fuzzy linguistic quantifier driven aggregation of trends (partial scores) via the traditional zadeh calculus of linguistically quantified propositions and the sugeno integral. Here we use for this purpose the choquet integral that has been widely advocated for many decision analytic and economic problems. The results are intuitively appealing and the method is effective and efficient.keywordslinguistic termmean absolute deviationfuzzy measurelinguistic labelpartial scorethese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
U2 - 10.1007/978-3-540-72950-1_29
DO - 10.1007/978-3-540-72950-1_29
M3 - Paper
SP - 284
EP - 294
ER -