Increasingly, in our everyday lives, we rely on our ability to access and understand complex information. Just as the search engine played a key role in helping people access relevant information, there is evidence that the next generation of information tools will provide users with a greater ability to analyse and make sense of large amounts of raw data. Visualization technologies are set to play an important role in this regard. However, the current generation of visualization tools are simply too complex for the typical user. In this paper we describe a novel application of case-based reasoning techniques to help users visualize complex datasets. We exploit an online visualization service, ManyEyes, and explore how case-based representation of datasets including simple features such as size and content types can produce recommendations to assist novice users in the selection of appropriate visualization types.
%0 Book Section
%1 citeulike:10429875
%A Freyne, Jill
%A Smyth, Barry
%B Lecture Notes in Computer Science
%C Berlin, Heidelberg
%D 2010
%E Bichindaritz, Isabelle
%E Montani, Stefania
%I Springer Berlin / Heidelberg
%K recommender visualization
%P 111--125
%R 10.1007/978-3-642-14274-1_10
%T Visualization for the Masses: Learning from the Experts Case-Based Reasoning. Research and Development
%U http://dx.doi.org/10.1007/978-3-642-14274-1_10
%V 6176
%X Increasingly, in our everyday lives, we rely on our ability to access and understand complex information. Just as the search engine played a key role in helping people access relevant information, there is evidence that the next generation of information tools will provide users with a greater ability to analyse and make sense of large amounts of raw data. Visualization technologies are set to play an important role in this regard. However, the current generation of visualization tools are simply too complex for the typical user. In this paper we describe a novel application of case-based reasoning techniques to help users visualize complex datasets. We exploit an online visualization service, ManyEyes, and explore how case-based representation of datasets including simple features such as size and content types can produce recommendations to assist novice users in the selection of appropriate visualization types.
%& 10
%@ 978-3-642-14273-4
@incollection{citeulike:10429875,
abstract = {{Increasingly, in our everyday lives, we rely on our ability to access and understand complex information. Just as the search engine played a key role in helping people access relevant information, there is evidence that the next generation of information tools will provide users with a greater ability to analyse and make sense of large amounts of raw data. Visualization technologies are set to play an important role in this regard. However, the current generation of visualization tools are simply too complex for the typical user. In this paper we describe a novel application of case-based reasoning techniques to help users visualize complex datasets. We exploit an online visualization service, ManyEyes, and explore how case-based representation of datasets including simple features such as size and content types can produce recommendations to assist novice users in the selection of appropriate visualization types.}},
added-at = {2018-03-19T12:24:51.000+0100},
address = {Berlin, Heidelberg},
author = {Freyne, Jill and Smyth, Barry},
biburl = {https://www.bibsonomy.org/bibtex/227f4d6986a052e60d8593523d0fd1921/aho},
chapter = 10,
citeulike-article-id = {10429875},
citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-14274-1_10},
citeulike-linkout-1 = {http://www.springerlink.com/content/j410502254708117},
doi = {10.1007/978-3-642-14274-1_10},
editor = {Bichindaritz, Isabelle and Montani, Stefania},
interhash = {88805e9c01ff2a9d90e0270e919a6bdf},
intrahash = {27f4d6986a052e60d8593523d0fd1921},
isbn = {978-3-642-14273-4},
keywords = {recommender visualization},
pages = {111--125},
posted-at = {2012-03-09 03:20:02},
priority = {2},
publisher = {Springer Berlin / Heidelberg},
series = {Lecture Notes in Computer Science},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{Visualization for the Masses: Learning from the Experts Case-Based Reasoning. Research and Development}},
url = {http://dx.doi.org/10.1007/978-3-642-14274-1_10},
volume = 6176,
year = 2010
}