Journal ArticleDOI
Linguistic query answering on data cubes with time dimension
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TLDR
A methodology for providing linguistic answers to queries involving the comparison of time series obtained from data cubes with time dimension, based on linguistically quantified statements and pointwise definitions of the degree and sign of local change is proposed.Abstract:
In this paper, we propose a methodology for providing linguistic answers to queries involving the comparison of time series obtained from data cubes with time dimension. Time series related to events which are interesting for the user are obtained by querying data cubes using OnLine Analytical Processing (OLAP) operations on the time dimension. The comparison of these query results can be summarized so that an appropriate short linguistic description of the series is provided to the user. Our approach is based on linguistically quantified statements and pointwise definitions of the degree and sign of local change. Our linguistic summaries are well suited to be included in an interface layer of a data warehouse system, improving the quality of human-machine interaction and the understandability of the results. © 2011 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.read more
Citations
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An overview of methods for linguistic summarization with fuzzy sets
TL;DR: The aim of this paper is to review the state of art on linguistic summarization in the framework of fuzzy sets, focusing on the methods for evaluating linguistic summaries and the current applications, and to propose a taxonomy for the methods.
Journal ArticleDOI
On generating linguistic descriptions of time series
Nicolás Marín,Daniel Sánchez +1 more
TL;DR: This paper provides a general approach for the concepts and processes related to the generation of linguistic descriptions of time series, and incorporates as a core element a description model, which is based on three pillars: a knowledge representation formalism, an expression language, and a quality framework.
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Linguistic Prototypes for Data From Eldercare Residents
TL;DR: A model for the analysis of time series sensor data collected at an eldercare facility that builds sets of linguistic summaries from the sensor data that describe different events that may occur each night.
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Toward automatic generation of linguistic advice for saving energy at home
TL;DR: An adaptation of standard natural language generation methodologies to generate customized linguistic descriptions of data is presented, supported by the computational theory of perceptions which comes from the fuzzy sets and systems research field.
Journal ArticleDOI
An intelligent system for the acquisition and management of information from bill of quantities in building projects
TL;DR: i-BoQ, an intelligent system for retrieving and structuring data coming from BoQ, is presented and intelligent capabilities together with a friendly web-based application allow to easily acquire and manage integrated BoQ information for supporting decision making in the construction project management.
References
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The Balanced Scorecard: Translating Strategy Into Action
R.C. Dorf,M. Raitanen +1 more
TL;DR: The balanced scorecard translating strategy into action 1st edition Books as discussed by the authors is available at the online library and can be used to translate scorecards into action books for reading or reading everyday.
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A computational approach to fuzzy quantifiers in natural languages
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A new approach to the summarization of data
TL;DR: A new approach to the summarization of data based upon the theory of fuzzy subsets allows for a linguistic summary of the data and is useful for both numeric and nonnumeric data.
Journal ArticleDOI
Linguistic summaries of data using fuzzy logic
Janusz Kacprzyk,Ronald R. Yager +1 more
TL;DR: The issue of how to measure the goodness of a linguistic summary is concentrated on, and the use of an interactive approach in which the user indicates first the class of linguistic summaries of interest is advocated.
Journal ArticleDOI
Linguistic database summaries and their protoforms: towards natural language based knowledge discovery tools
TL;DR: An extension of the classic Yager's approach to involve more sophisticated criteria of goodness, search methods, etc, and shows how fuzzy queries are related to linguistic summaries, which makes it possible to implement such linguistic data summaries.