Linguistic local change comparison of time series

Castillo-Ortega, Rita; Mann, Nicolas; Sánchez, Daniel

doi:10.1109/fuzzy.2011.6007409

Cited by 15 publications

(14 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Linguistic summaries have been proven successful in various healthcare-related context, e.g., in [25,6,1,23]. For example, in [25], Wilbik et al focus on potential changes in time and introduce modication of summaries into the linguistic medoid prototypes, that may be exemplied with the following sentence: Mrs. Wilbewski is much better this week than she was last week.…”

Section: Related Workmentioning

confidence: 99%

Personalized linguistic summaries in smartphone-based monitoring of bipolar disorder patients

Kaczmarek-Majer¹,

Hryniewicz²,

Dominiak³

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

Personalized linguistic summaries are developed with the use of protoforms in the sense of Yager and Kacprzyk. We discuss the construction and usefulness of such patientdependent and disease-state-dependent linguistic summaries that may be examplied as Most outgoing calls in mania state (disease period) are short compared to the calls recorded in the euthymia state (healthy period). Such linguistic summaries may become important features in the smartphonebased monitoring of the bipolar disorder patients and inform about the detected change in patient's state. The main advantage of the personalized linguistic summaries is their human-centricity. The performance of the proposed approach is illustrated with examples based on the real-life data collected within the observational study.

show abstract

Section: Related Workmentioning

confidence: 99%

Personalized linguistic summaries in smartphone-based monitoring of bipolar disorder patients

Kaczmarek-Majer¹,

Hryniewicz²,

Dominiak³

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

show abstract

“…The flowchart of this method is shown in Figure 3. Castillo-Ortega et al 38,[80][81][82] extended previous linguistic summarization studies and compared two different time series according to the degree and the sign of local change in trends. The proposed method was applied to compare two different time series of patient inflow to a medical center and retail gasoline prices in New York and Texas during the same period of time.…”

Section: Type II Quantified Sentence: "Q W G (S G ) Ys Are/havementioning

confidence: 99%

Linguistic Summarization of Europe Brent Spot Price Time Series Along with the Interpretations from the Perspective of Turkey

Hatipoğlu

Boran

Avcı

et al. 2014

Int. J. Intell. Syst.

View full text Add to dashboard Cite

Compared to the predictive models for forecasting crude oil price, the descriptive models are also important for discovering the relations among factors that have influence on crude oil price. In this paper, linguistic summarization of time series, a descriptive technique, is used to summarize the Europe Brent Spot Price (EBSP) data (dollars per barrel) from May 1987 to July 2013 on daily and monthly base. This study is the first attempt in the literature for linguistic summarization of the EBSP time series with the aim to establish a decision support tool that can be used for generating linguistic propositions helping the estimation of future behaviors and fluctuations of oil price time series for oil‐importer countries such as Turkey. Economic interpretations of generated linguistic propositions about the main features of EBSP trends (duration, dynamics of change, and variability) and a procurement strategy, indicating that Turkey could cut back on oil importation about $573.88 million between 1996 and 2012, are suggested from the perspective of Turkey.

show abstract

“…It is also possible to compare time series based on the result of user defined queries over a data cube with time dimension. The similarity between time series is then described using local changes [14]. In [8] linguistic summaries of investment funds are obtained using a set of features to characterize the trends such as the slope of the line segment and study the description of duration and variability.…”

Section: Introductionmentioning

confidence: 99%

Linguistic summaries of categorical time series for septic shock patient data

Almeida

Lesot

Bouchon‐Meunier

et al. 2013

2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

View full text Add to dashboard Cite

Linguistic summarization is a data mining and knowledge discovery approach to extract patterns and sum up large volume of data into simple sentences. There is a large research in generating linguistic summaries which can be used to better understand and communicate about patterns, evolution and long trends in numerical, time series or labelled data. The objective of this work is to develop a computational system capable of automatically generating linguistic descriptions of time series data of septic shock patients containing labelled data, not only of the whole series, but also on the differences between subsets of the data. This is of particular interest in septic shock, as the differences between patients are not well understood. For this purpose we propose a new type of differential summaries, based on a numerical criterion assessing the characteristics of the summary on each subset of interest. Furthermore, this paper proposes an extension of linguistic summaries to provide temporal and categorical contextualization. This is of particular interest in healthcare to detect differences related to a condition or illness as well as the effectiveness of the administered treatment.

show abstract

Linguistic local change comparison of time series

Cited by 15 publications

References 36 publications

Personalized linguistic summaries in smartphone-based monitoring of bipolar disorder patients

Personalized linguistic summaries in smartphone-based monitoring of bipolar disorder patients

Linguistic Summarization of Europe Brent Spot Price Time Series Along with the Interpretations from the Perspective of Turkey

Linguistic summaries of categorical time series for septic shock patient data

Contact Info

Product

Resources

About