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An overview of intelligent data assistants for data analysis


Serban, F; Kietz, J U; Bernstein, A (2010). An overview of intelligent data assistants for data analysis. In: 3rd Planning to Learn Workshop (WS9) at ECAI'10, Lisbon, Portugal, 16 August 2010 - 20 August 2010, 7-14.

Abstract

Today's intelligent data assistants (IDA) for data analysis are focusing on how to do effective and intelligent data analysis. However this is not a trivial task since one must take into consideration all the influencing factors: on one hand data analysis in general and on the other hand the communication and interaction with data analysts. The basic approach of building an IDA, where data analysis is (1) better as well as (2) faster in the same time, is not a very rewarding criteria and does not help in designing good IDAs. Therefore this paper tries to (a) discover constructive criteria that allow us to compare existing systems and help design better IDAs and (b) review all previous IDAs based on these criteria to find out what are the problems that IDAs should solve as well as which method works best for which problem. In conclusion we try to learn from previous experiences what features should be incorporated into a new IDA that would solve the problems of today's analysts.

Today's intelligent data assistants (IDA) for data analysis are focusing on how to do effective and intelligent data analysis. However this is not a trivial task since one must take into consideration all the influencing factors: on one hand data analysis in general and on the other hand the communication and interaction with data analysts. The basic approach of building an IDA, where data analysis is (1) better as well as (2) faster in the same time, is not a very rewarding criteria and does not help in designing good IDAs. Therefore this paper tries to (a) discover constructive criteria that allow us to compare existing systems and help design better IDAs and (b) review all previous IDAs based on these criteria to find out what are the problems that IDAs should solve as well as which method works best for which problem. In conclusion we try to learn from previous experiences what features should be incorporated into a new IDA that would solve the problems of today's analysts.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:20 August 2010
Deposited On:24 Feb 2011 15:25
Last Modified:05 Apr 2016 14:44
Other Identification Number:1424
Permanent URL: https://doi.org/10.5167/uzh-44847

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