Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1504/IJMSO.2016.081584 | IJMSO |
Field | DocType | Volume |
Data mining,Faceted search,Information retrieval,Computer science,Species identification,Sequent,Casual,FishBase | Journal | 11 |
Issue | ISSN | Citations |
3 | 1744-2621 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yannis Tzitzikas | 1 | 773 | 82.04 |
| Nicolas Bailly | 2 | 3 | 1.07 |
| Panagiotis Papadakos | 3 | 122 | 14.40 |
| Nikos Minadakis | 4 | 54 | 7.09 |
| George Nikitakis | 5 | 2 | 0.70 |