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Journal of Intelligent Information Systems

Erschienen in:

01.06.2012

In & out zooming on time-aware user/tag clusters

verfasst von: Eirini Giannakidou, Vassiliki Koutsonikola, Athena Vakali, Ioannis Kompatsiaris

Erschienen in: Journal of Intelligent Information Systems | Ausgabe 3/2012

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Abstract

The common ground behind most approaches that analyze social tagging systems is addressing the information challenge that emerges from the massive activity of millions of users who interact and share resources and/or metadata online. However, lack of any time-related data in the analysis process implicitly denies much of the dynamic nature of social tagging activity. In this paper we claim that holding a temporal dimension, allows for tracking macroscopic and microscopic users’ interests, detecting emerging trends and recognizing events. To this end, we propose a time-aware co-clustering approach for acquiring semantic and temporal patterns out of the tagging activity. The resulted clusters contain both users and tags of similar patterns over time, and reveal non-obvious or “hidden” relations among users and topics of their common interest. Zoom in & out views serve as visualization methods on different aspects of the clusters’ structure, in order to evaluate the efficiency of the approach.

Vorheriger Artikel A new unsupervised feature selection method for text clustering based on genetic algorithms

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As tag similarity refers mostly to tags’ conceptual similarity, we will pertain to tag-based similarity as semantic similarity, throughout the article.

The potential applications of tracking such clusters are discussed in the next section.

This is not imprinted in Fig. 3 for clarity reasons.

Each time frame corresponds to 10 days duration, at the particular time scale.

Each time frame corresponds to 1 day duration, at the particular time scale.

Although the approach in Becker et al. (2010) is more related to our approach than the other ones presented, still there cannot be a direct comparison between the two methods, since the one mines resources, whereas the other groups together tags and users.

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Titel: In & out zooming on time-aware user/tag clusters
verfasst von: Eirini Giannakidou
Vassiliki Koutsonikola
Athena Vakali
Ioannis Kompatsiaris
Publikationsdatum: 01.06.2012
Verlag: Springer US
Erschienen in: Journal of Intelligent Information Systems / Ausgabe 3/2012
Print ISSN: 0925-9902
Elektronische ISSN: 1573-7675
DOI: https://doi.org/10.1007/s10844-011-0173-4

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