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 |
| State | Published - Mar 1998 |
| Externally published | Yes |
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Keywords
- Artificial intelligence
- Data exploration
- Planning
ASJC Scopus subject areas
- Artificial Intelligence
Cite this
Interaction with a mixed-initiative system for exploratory data analysis. / St. Amant, Robert; Cohen, Paul R.
In: Knowledge-Based Systems, Vol. 10, No. 5, 03.1998, p. 265-273.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Interaction with a mixed-initiative system for exploratory data analysis
AU - St. Amant, Robert
AU - Cohen, Paul R
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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M3 - Article
AN - SCOPUS:0032023020
VL - 10
SP - 265
EP - 273
JO - Knowledge-Based Systems
JF - Knowledge-Based Systems
SN - 0950-7051
IS - 5
ER -