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SAES: An Introduction to Self-Adapting Exploratory Structures

Dipartimento di Informatica, Universita’ degli Studi di Torino, I-10124 Torino, Italy
Future Internet 2019, 11(3), 54; https://doi.org/10.3390/fi11030054
Received: 31 December 2018 / Revised: 10 February 2019 / Accepted: 19 February 2019 / Published: 26 February 2019
(This article belongs to the Special Issue 10th Anniversary Feature Papers)
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PDF [196 KB, uploaded 26 February 2019]

Abstract

Self-adapting exploratory structures (SAESs) are the basic components of exploratory search. They are abstract structures which allow searching or querying of an information base and summarizing of results using a uniform representation. A definition and a characterization of SAES is given, as well as a discussion of structures that are SAES or can be modified in order to become SAES. These include dynamic taxonomies (also known as faceted search), tag clouds, continuous sliders, geographic maps, and dynamic clustering methods, such as Scatter-Gather. Finally, the integration of these structures into a single interface is discussed. View Full-Text
Keywords: exploratory search; dynamic taxonomies; faceted search; tag clouds; Scatter-Gather exploratory search; dynamic taxonomies; faceted search; tag clouds; Scatter-Gather
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Sacco, G.M. SAES: An Introduction to Self-Adapting Exploratory Structures. Future Internet 2019, 11, 54.

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