Interaction with a mixed-initiative system for exploratory data analysis

Robert St. Amant; Paul R. Cohen

doi:10.1016/s0950-7051(97)00038-5

Interaction with a mixed-initiative system for exploratory data analysis

Robert St. Amant, Paul R. Cohen

Sciences Technology and Arts, School of

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Exploratory data analysis (EDA) plays an increasingly important role in statistical analysis. EDA is difficult, however, even with the help of modern statistical software. We have developed an assistant for data exploration, based on AI planning techniques, that addresses some of the strategic shortcomings of conventional software. This paper describes the design and behavior of the system and discusses an experimental evaluation that demonstrates the effectiveness of our approach.

Original language	English (US)
Pages (from-to)	265-273
Number of pages	9
Journal	Knowledge-Based Systems
Volume	10
Issue number	5
DOIs	https://doi.org/10.1016/s0950-7051(97)00038-5
State	Published - Mar 1998

Keywords

Artificial intelligence
Data exploration
Planning

ASJC Scopus subject areas

Management Information Systems
Software
Information Systems and Management
Artificial Intelligence

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10.1016/s0950-7051(97)00038-5

Cite this

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title = "Interaction with a mixed-initiative system for exploratory data analysis",

abstract = "Exploratory data analysis (EDA) plays an increasingly important role in statistical analysis. EDA is difficult, however, even with the help of modern statistical software. We have developed an assistant for data exploration, based on AI planning techniques, that addresses some of the strategic shortcomings of conventional software. This paper describes the design and behavior of the system and discusses an experimental evaluation that demonstrates the effectiveness of our approach.",

keywords = "Artificial intelligence, Data exploration, Planning",

author = "{St. Amant}, Robert and Cohen, {Paul R.}",

note = "Funding Information: This research was supported by ARPA/Rome Laboratory under contract No. F30602-93-0100 and by the Department of the Army, Army Research Office, under contract No. DAAH04-95-1-0466. The US Government is authorized to reproduce and distribute reprints for governmental purposes not withstanding any copyright notation hereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements either expressed or implied, of the Advanced Research Projects Agency, Rome Laboratory, or the US Government.",

year = "1998",

month = mar,

doi = "10.1016/s0950-7051(97)00038-5",

language = "English (US)",

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TY - JOUR

T1 - Interaction with a mixed-initiative system for exploratory data analysis

AU - St. Amant, Robert

AU - Cohen, Paul R.

N1 - Funding Information: This research was supported by ARPA/Rome Laboratory under contract No. F30602-93-0100 and by the Department of the Army, Army Research Office, under contract No. DAAH04-95-1-0466. The US Government is authorized to reproduce and distribute reprints for governmental purposes not withstanding any copyright notation hereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements either expressed or implied, of the Advanced Research Projects Agency, Rome Laboratory, or the US Government.

PY - 1998/3

Y1 - 1998/3

N2 - Exploratory data analysis (EDA) plays an increasingly important role in statistical analysis. EDA is difficult, however, even with the help of modern statistical software. We have developed an assistant for data exploration, based on AI planning techniques, that addresses some of the strategic shortcomings of conventional software. This paper describes the design and behavior of the system and discusses an experimental evaluation that demonstrates the effectiveness of our approach.

AB - Exploratory data analysis (EDA) plays an increasingly important role in statistical analysis. EDA is difficult, however, even with the help of modern statistical software. We have developed an assistant for data exploration, based on AI planning techniques, that addresses some of the strategic shortcomings of conventional software. This paper describes the design and behavior of the system and discusses an experimental evaluation that demonstrates the effectiveness of our approach.

KW - Artificial intelligence

KW - Data exploration

KW - Planning

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Interaction with a mixed-initiative system for exploratory data analysis

Abstract

Keywords

ASJC Scopus subject areas

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