Title: Social linkage and ranking model for tags-based resources

Authors: Amel Benna; Hakima Mellah

Addresses: Research Center on Scientific and Technical Information (CERIST), 05, rue des 03 Frères Aissiou, BP 143, BenAknoun, 16030 Algiers, Algeria; Computer Science Department, LSI Laboratory, Houari Boumediene University of Science and Technology (USTHB), BP 32, El-Alia Bab-Ezzouar, 16111, Algiers, Algeria ' Research Center on Scientific and Technical Information (CERIST), 05, rue des 03 Frères Aissiou, BP 143, BenAknoun, 16030 Algiers, Algeria; ESI, BP 68M, Oued Smar, 16309, Algiers, Algeria

Abstract: With the proliferation of social media, it is becoming important to support a significant amount of user tags in selecting the most appropriate resource description during the search process. In this paper, we propose to identify and structure the links between resources by taking into account a resource social dimension. Each resource is assigned to a cluster of tags hierarchy. The clusters of tags are formed by a classification method while the hierarchical classification of tags within clusters is defined using a hierarchy classification algorithm. User's query is expanded by a social dimension and the clusters of tags are used to facilitate the search and ranking process. The results of our experiment, crawled from Delicious Folksonomy, demonstrate significant improvement over traditional retrieval approaches.

Keywords: social linkage; collaborative tagging; social ranking; social context; user tags; resource descriptions; search process; tag clusters; classification; social media.

DOI: 10.1504/IJMSO.2013.057764

International Journal of Metadata, Semantics and Ontologies, 2013 Vol.8 No.3, pp.236 - 244

Received: 07 Feb 2013
Accepted: 26 Jun 2013
Published online: 14 Oct 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article