Faceted Ranking of Egos in Collaborative Tagging Systems

Multimedia uploaded content is tagged and recommended by users of collaborative systems, resulting in informal classifications also known as folksonomies. Faceted web ranking has been proved a reasonable alternative to a single ranking which does not take into account a personalized context. In this...

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Bibliographic Details
Published inarXiv.org
Main Authors Orlicki, Jose Ignacio, Fierens, Pablo Ignacio, Alvarez-Hamelin, José Ignacio
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 26.09.2008
Subjects
Algorithms
Collaboration
Computation
Empirical analysis
Graph theory
Multimedia
Ranking
Search engines
Tags
Online AccessGet full text

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Summary:Multimedia uploaded content is tagged and recommended by users of collaborative systems, resulting in informal classifications also known as folksonomies. Faceted web ranking has been proved a reasonable alternative to a single ranking which does not take into account a personalized context. In this paper we analyze the online computation of rankings of users associated to facets made up of multiple tags. Possible applications are user reputation evaluation (ego-ranking) and improvement of content quality in case of retrieval. We propose a solution based on PageRank as centrality measure: (i) a ranking for each tag is computed offline on the basis of the corresponding tag-dependent subgraph; (ii) a faceted order is generated by merging rankings corresponding to all the tags in the facet. The fundamental assumption, validated by empirical observations, is that step (i) is scalable. We also present algorithms for part (ii) having time complexity O(k), where k is the number of tags in the facet, well suited to online computation.
ISSN:2331-8422