An approach to deriving a virtual thematic folksonomy based system from a social inter-folksonomy based scenario

The diffusion of social networks has stimulated folksonomy-based systems hereafter, folk-systems to equip themselves with functionalities for the management of social relationships among users. This suggests that folk-systems and social networks have many “points of contact”. At the same time, social networks are evolving toward social internetworking systems, i.e. systems where several social networks are simultaneously considered and where users are allowed to interact with each other, even if they belong to different social networks. This trend, presumably, could extend to folk-systems. In this paper, we investigate this issue. In particular, first we introduce the concept of social inter-folksonomy based systems hereafter, SIFS; after this, we introduce a hypergraph-based model to represent and handle a SIFS. Finally, we present an approach for the derivation of a virtual thematic folk-system from a SIFS, i.e. a fragment of SIFS centered on one or more topics which has all the properties and the functionalities of a real folk-system.

[1]  Cong Yu,et al.  From del.icio.us to x.qui.site: recommendations in social tagging sites , 2008, SIGMOD Conference.

[2]  Alexandre Passant,et al.  Combining Social Music and Semantic Web for Music-related Recommender Systems , 2008, SDoW@ISWC.

[3]  Yong Yu,et al.  Optimizing web search using social annotations , 2007, WWW '07.

[4]  Katarzyna Musial,et al.  User position measures in social networks , 2009, SNA-KDD '09.

[5]  S. Wasserman,et al.  Models and methods in social network analysis , 2005 .

[6]  Giovanni Quattrone,et al.  Exploitation of semantic relationships and hierarchical data structures to support a user in his annotation and browsing activities in folksonomies , 2009, Inf. Syst..

[7]  Richi Nayak,et al.  Personalized Recommender Systems Integrating Social Tags and Item Taxonomy , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[8]  Enrico Motta,et al.  Integrating Folksonomies with the Semantic Web , 2007, ESWC.

[9]  Antonino Nocera,et al.  Recommendation of similar users, resources and social networks in a Social Internetworking Scenario , 2011, Inf. Sci..

[10]  Wan-Shiou Yang,et al.  Discovering cohesive subgroups from social networks for targeted advertising , 2008, Expert Syst. Appl..

[11]  George A. Vouros,et al.  Learning subsumption hierarchies of ontology concepts from texts , 2010, Web Intell. Agent Syst..

[12]  Avare Stewart,et al.  Cross-tagging for personalized open social networking , 2009, HT '09.

[13]  Giovanni Quattrone,et al.  Finding reliable users and social networks in a social internetworking system , 2009, IDEAS '09.

[14]  Feng Luo,et al.  Exploring Local Community Structures in Large Networks , 2006, 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06).

[15]  Antonino Nocera,et al.  Recommendation of reliable users, social networks and high-quality resources in a Social Internetworking System , 2011, AI Commun..

[16]  Rui Li,et al.  Towards effective browsing of large scale social annotations , 2007, WWW '07.

[17]  Giovanna Castellano,et al.  Computational Intelligence techniques for Web personalization , 2008, Web Intell. Agent Syst..

[18]  Yiyu Yao,et al.  VisiQ: Supporting visual and interactive query refinement , 2007, Web Intell. Agent Syst..

[19]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[20]  Yuxiang Sun,et al.  Identifying a hierarchy of bipartite subgraphs for web site abstraction , 2007, Web Intell. Agent Syst..

[21]  Martin Szomszor,et al.  Correlating user profiles from multiple folksonomies , 2008, Hypertext.

[22]  Peter Mika,et al.  Ontologies are us: A unified model of social networks and semantics , 2005, J. Web Semant..

[23]  Bernardo A. Huberman,et al.  Usage patterns of collaborative tagging systems , 2006, J. Inf. Sci..

[24]  Panagiotis Symeonidis,et al.  A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis , 2010, IEEE Transactions on Knowledge and Data Engineering.

[25]  Thomas Hofmann,et al.  Probabilistic Latent Semantic Analysis , 1999, UAI.

[26]  Lars Schmidt-Thieme,et al.  Tag-aware recommender systems by fusion of collaborative filtering algorithms , 2008, SAC '08.

[27]  Pablo Gervás,et al.  Personalisation in news delivery systems: Item summarization and multi-tier item selection using relevance feedback , 2005, Web Intell. Agent Syst..

[28]  Jon Iturrioz Towards federated Web2.0 sites: the TAGMAS approach , 2007 .

[29]  John G. Breslin,et al.  Weaving SIOC into the Web of Linked Data , 2008, LDOW.

[30]  Nan Du,et al.  Improved recommendation based on collaborative tagging behaviors , 2008, IUI '08.

[31]  David R. Millen,et al.  Dogear: Social bookmarking in the enterprise , 2006, CHI.

[32]  Ali A. Ghorbani,et al.  The ACORN multi-agent system , 2003, Web Intell. Agent Syst..

[33]  E A Leicht,et al.  Community structure in directed networks. , 2007, Physical review letters.

[34]  Xavier Serra,et al.  FOAFing the music: Bridging the semantic gap in music recommendation , 2008, J. Web Semant..

[35]  Giovanni Quattrone,et al.  A query expansion and user profile enrichment approach to improve the performance of recommender systems operating on a folksonomy , 2010, User Modeling and User-Adapted Interaction.

[36]  Licia Capra,et al.  Social ranking: uncovering relevant content using tag-based recommender systems , 2008, RecSys '08.

[37]  Kristina Lerman,et al.  Personalizing Image Search Results on Flickr , 2007, ArXiv.