Title: Using preference-enriched faceted search for species identification

Authors: Yannis Tzitzikas; Nicolas Bailly; Panagiotis Papadakos; Nikos Minadakis; George Nikitakis

Addresses: Institute of Computer Science, FORTH, Crete, Greece; Computer Science Department, University of Crete, Crete, Greece ' Hellenic Centre for Marine Research, Crete, Greece ' Institute of Computer Science, FORTH, Crete, Greece ' Institute of Computer Science, FORTH, Crete, Greece ' Computer Science Department, University of Crete, Crete, Greece

Abstract: Species identification is essentially a decision-making process comprising steps in which the user makes a selection of characters, figures or photographs, or provides an input, that restricts other choices, until reaching one species. In some identification methods such decisions should have a specific order. Consequently, a wrong decision at the beginning of the process, could exclude a big set of options. To make this process more flexible and less vulnerable to wrong decisions, in this paper we investigate how a Preference-enriched Faceted Search (PFS) process can be used to aid the identification of species. We show how the proposed process covers and advances the existing methods and we report our experience from applying this process over data taken from FishBase. In the sequent, we elaborate on evaluation and we report the results of a task-based evaluation that shows that the PFS-based method can be used effectively by casual users.

Keywords: species identification; identification tasks; faceted search; user preferences; fisheries; fish sepcies.

DOI: 10.1504/IJMSO.2016.081584

International Journal of Metadata, Semantics and Ontologies, 2016 Vol.11 No.3, pp.165 - 179

Received: 26 May 2016
Accepted: 02 Oct 2016

Published online: 16 Jan 2017 *

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