Mining time series data by a fuzzy linguistic summary system
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An overview of methods for linguistic summarization with fuzzy sets
2016, Expert Systems with ApplicationsCitation Excerpt :The linguistic summarization is capable of extracting potential useful and abstract knowledge from both numeric and categoric data. Therefore, it has received a great deal of attention from a diversity of areas including time series mining (Batyrshin & Sheremetov, 2008; Castillo-Ortega, Marin, & Sanchez, 2011a; 2011b; Chiang, Chow, & Wang, 2000; Kacprzyk, Wilbik, & Zadrozny, 2008; 2010), decision support systems (Kacprzyk & Zadrozny, 2010b), human activity (Anderson et al., 2009; 2012), financial reports (Mendez-Nunez & Trivino, 2010), energy (van der Heide & Trivio, 2009), traffic analysis (Alvarez-Alvarez, Sanchez-Valdes, Trivino, Sanchez, & Suarez, 2012; Trivino et al., 2010), social network (Yager & Yager, 2012; Yager, 2010), recommender systems (Carrasco & Villar, 2012; Pigeau, Raschia, Gelgon, Mouaddib, & Saint-Paul, 2003), driving activity (Eciolaza, Pereira-Faria, & Trivino, 2012) and so on. Despite the fast development in the field, there exists only one comprehensive study of Delgado, Ruiz, Sanchez, and Vila (2014) focusing on fuzzy quantification approaches, their comparisons and the links between them.
New statistical analysis in marketing research with fuzzy data
2016, Journal of Business ResearchCitation Excerpt :Building on the similarity of the linguistic concept, they present a formula of fuzzy association degree. Carlsson and Fuller (2000a); Carlsson and Fuller (2000b); Chiang, Chow, and Wang (2000), and Herrera and Herrera-Viedma (2000) discussed many concepts regarding the computation of fuzzy linguistic worthy broadcasting. Drawing from previous statements: (1) the methods of traditional statistical analysis and measurement used in public consensus are incomplete.
Transcribing Debussy's Syrinx dynamics through Linguistic Description: The MUDELD algorithm
2016, Fuzzy Sets and SystemsCitation Excerpt :Alternatively to statistical studies, Batyrshin et al. [18] advocated for the extraction of rule-based descriptions of time series using linguistic shape descriptors. Chiang, Chow and Wang [19] proposed a novel method for mining time series capable of overcoming the problem of having points very close or even equal to each other. In this line, Kacprzyk, Wilbik and Zadrożny [17] described a procedure to summarize temporal trends, identified with straight line segments of a piecewise linear.
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2016, Information SciencesCitation Excerpt :The system interacts with the user by means of a graphical tool used to run a preliminary process of analysis of database information in order to determine potentially what type of knowledge could be discovered. The model is used to predict the online use of different computer resources, including CPU and storage devices [16]. Abonyi et al. were, as far as we know, the first to use the two PCA (principal component analysis) related statistics as cost functions in a bottom-up segmentation algorithm.
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