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Evaluation of Hierarchical Clustering via Markov Decision Processes for Efficient Navigation and Search

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Author(s)
Moreno, Raul 
Huáng, WÄ›ipéng 
Younus, Arjumand 
O'Mahony, Michael P. 
Hurley, Neil J. 
Uri
http://hdl.handle.net/10197/9169
Date Issued
14 September 2017
Date Available
15T13:23:03Z January 2018
Abstract
In this paper, we propose a new evaluation measure to assessthe quality of a hierarchy in supporting search queries to content collections.The evaluation measure models the scenario of a searcher seeking a particular target item in the hierarchy. It takes into account the structureof the hierarchy by measuring the cognitive challenge of determiningthe correct path in the hierarchy as well as the reduction in search timeaorded by hierarchy. The goal is to propose a general-purpose measurethat can be applied in dierent application contexts, allowing dierenthierarchical arrangements of content to be quantitatively assessed
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Springer
Series
Lecture Notes in Computer Science book series (LNCS, volume 10456)
Copyright (Published Version)
2017 Springer
Keywords
  • Markov decision proce...

  • Hierarchy navigation

DOI
10.1007/978-3-319-65813-1_12
Language
English
Status of Item
Peer reviewed
Description
8th International Conference of the CLEF Association, CLEF 2017, Dublin, Ireland, September 11–14 2017
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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Insight Research Collection
Scopus© citations
1
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