Generation of prototypes from sets of linguistic summaries

Anna Wilbik; James M. Keller; James C. Bezdek

doi:10.1109/FUZZ-IEEE.2012.6250831

Generation of prototypes from sets of linguistic summaries

Anna Wilbik, James M. Keller, James C. Bezdek

Research output: Contribution to conference › Paper › Academic

Abstract

Linguistic summarization of time series can glean meaningful information from huge amounts of data. However, in situations like continuous monitoring, even linguistic summaries become difficult for a person to understand. In this paper, we develop an approach to generate linguistic prototypes from a group of time blocks that represent a normal condition. Then the set of summaries for new time blocks are compared to the prototypes to flag anomalous conditions, thereby reducing the burden on the human. Case studies from an eldercare environment demonstrate the utility of this approach.

Original language	English
Pages	1-8
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2012.6250831
Publication status	Published - 2012
Externally published	Yes

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10.1109/FUZZ-IEEE.2012.6250831

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AB - Linguistic summarization of time series can glean meaningful information from huge amounts of data. However, in situations like continuous monitoring, even linguistic summaries become difficult for a person to understand. In this paper, we develop an approach to generate linguistic prototypes from a group of time blocks that represent a normal condition. Then the set of summaries for new time blocks are compared to the prototypes to flag anomalous conditions, thereby reducing the burden on the human. Case studies from an eldercare environment demonstrate the utility of this approach.

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Generation of prototypes from sets of linguistic summaries

Abstract

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