Evaluation of a semi-autonomous assistant for exploratory data analysis

Robert St. Amant, Paul R. Cohen

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations

Abstract

AIDE is a knowledge-based planning assistant for intelligent data exploration that draws on research in mixed-initiative planning and collaborative systems. AIDE incrementally explores a dataset, guided by user directives and its own evaluation of the data. The system is mixed-initiative: it semi-autonomously pursues high- and low-level goals but allows the user to review and potentially override its decisions. This paper briefly describes the exploratory task, AIDE's architecture, and how the system interacts with the user. The bulk of the paper is devoted to an experiment in which we compared the performance of human subjects analyzing data with and without AIDE. Although subjects each worked with AIDE for only a few hours, the system clearly influenced the efficiency and coherence of their exploration. We surmise that AIDE facilitates data analysis primarily by helping analysts navigate through the large space of decisions involved in exploring a dataset.

Original languageEnglish (US)
Pages355-362
Number of pages8
DOIs
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 1st International Conference on Autonomous Agents - Marina del Rey, CA, USA
Duration: Feb 5 1997Feb 8 1997

Other

OtherProceedings of the 1997 1st International Conference on Autonomous Agents
CityMarina del Rey, CA, USA
Period2/5/972/8/97

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Evaluation of a semi-autonomous assistant for exploratory data analysis'. Together they form a unique fingerprint.

Cite this