Interpreting and explaining pagerank through argumentation semantics
File(s)2021___Intel__Artif__AIxIA___PageRank_Journal (5).pdf (1.79 MB)
Accepted version
Author(s)
Albini, Emanuele
Baroni, Pietro
Rago, Antonio
Toni, Francesca
Type
Journal Article
Abstract
In this paper we show how re-interpreting PageRank as an argumentation semantics for a bipolar argumentation framework empowers its explainability. After showing that PageRank, naively re-interpreted as an argumentation semantics for support frameworks, fails to satisfy some generally desirable properties, we propose a novel approach able to reconstruct PageRank as a gradual semantics of a suitably defined bipolar argumentation framework, while satisfying these properties. We then show how the theoretical advantages afforded by this approach also enjoy an enhanced explanatory power: we propose several types of argument-based explanations for PageRank, each of which focuses on different aspects of the algorithm and uncovers information useful for the comprehension of its results.
Date Issued
2021-07-28
Date Acceptance
2021-07-01
Citation
Intelligenza Artificiale, 2021, 15 (1), pp.17-34
ISSN
1724-8035
Publisher
IOS Press
Start Page
17
End Page
34
Journal / Book Title
Intelligenza Artificiale
Volume
15
Issue
1
Copyright Statement
© 2014 – IOS Press and the authors. All rights reserved. The definitive, peer reviewed and edited version of this article is published in [Intelligenza Artificiale, 15, 1, 17-34,
DOI: 10.3233/IA-210095
DOI: 10.3233/IA-210095
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000680740500002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
ACCEPTABILITY
Computer Science
Computer Science, Artificial Intelligence
explainability
gradual argumentation semantics
PageRank
quantitative bipolar argumentation frameworks
Science & Technology
Technology
Publication Status
Published
Date Publish Online
2021-07-28