research-article

A survey of intelligent assistants for data analysis

Authors:

Floarea Serban,

Joaquin Vanschoren,

Jörg-Uwe Kietz,

Abraham BernsteinAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 45, Issue 3

Article No.: 31, Pages 1 - 35

https://doi.org/10.1145/2480741.2480748

Published: 03 July 2013 Publication History

Abstract

Research and industry increasingly make use of large amounts of data to guide decision-making. To do this, however, data needs to be analyzed in typically nontrivial refinement processes, which require technical expertise about methods and algorithms, experience with how a precise analysis should proceed, and knowledge about an exploding number of analytic approaches. To alleviate these problems, a plethora of different systems have been proposed that “intelligently” help users to analyze their data.

This article provides a first survey to almost 30 years of research on intelligent discovery assistants (IDAs). It explicates the types of help IDAs can provide to users and the kinds of (background) knowledge they leverage to provide this help. Furthermore, it provides an overview of the systems developed over the past years, identifies their most important features, and sketches an ideal future IDA as well as the challenges on the road ahead.

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A survey of intelligent assistants for data analysis

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 45, Issue 3

June 2013

575 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/2480741

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Published: 03 July 2013

Accepted: 01 February 2012

Revised: 01 January 2012

Received: 01 August 2011

Published in CSUR Volume 45, Issue 3

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Tianxing MZhukova NJiafeng YLebedev S(2022)An Architecture of the Semantic Meta Mining Assistant for Adaptive Domain-Oriented Data ProcessingInternational Journal of Embedded and Real-Time Communication Systems10.4018/IJERTCS.30211113:1(1-38)Online publication date: 29-Jun-2022
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