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

Author(s)
Moreno, Raul  
Huáng, Wěipéng  
Younus, Arjumand  
O'Mahony, Michael P.  
Hurley, Neil J.  
Uri
http://hdl.handle.net/10197/9169
Date Issued
2017-09-14
Date Available
2018-01-15T13:23:03Z
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
Subjects

Markov decision proce...

Hierarchy navigation

DOI
10.1007/978-3-319-65813-1_12
Language
English
Status of Item
Peer reviewed
Conference Details
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_publication.pdf

Size

1.15 MB

Format

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Checksum (MD5)

0d11275b6a86e0d5c39081e473a05177

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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