Collective annotation: perspectives for information retrieval improvement

Authors:
Guillaume Cabanac;Max Chevalier;Claude Chrisment;Christine Julien
Affiliations:
Université Toulouse, Toulouse cedex;Université Toulouse, Toulouse cedex and IUT Rangueil, Toulouse cedex;Université Toulouse, Toulouse cedex;Université Toulouse, Toulouse cedex
Venue:
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Year:
2007

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Abstract

Nowadays we enter the Web 2.0 era where people's participation is a key principle. In this context, collective annotations enable to share and discuss readers' feedback with regard to digital documents. The results of this activity are going to be used in the Information Retrieval context, which already tends to harness similar collective contributions. In this paper, we propose a collective annotation model supporting feedback exchange through discussion threads. Considering this model, we associate annotations with a measure of the sparked consensus degree (social validation), this allows to provide a synthesized view of associated discussions. Finally, we investigate how Information Retrieval systems may benefit from the proposed model, thus taking advantage of human-contributed highly value-added information, namely collective annotations.