Know the Right People? Recommender Systems for Web 2.0

Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular online communities for creating, editing and sharing content. However, the rapid increase in size of online communities and the availability of large amounts of shared data make discovering relevant content and finding related users a difficult task. Web 2.0 applications provide a rich set of structures and annotations that can be mined for a variety of purposes. In this paper we propose a formal model to characterize users, items, and annotations in Web 2.0 environments. Based on this model we propose recommendation mechanisms using methods from social network analysis, collaborative filtering, and machine learning. Our objective is to construct collaborative recommender systems that predict the utility of items, users or groups based on the multi-dimensional social environment of a given user.

[1]  Ravi Kumar,et al.  Visualizing tags over time , 2006, WWW '06.

[2]  D. Watts,et al.  Small Worlds: The Dynamics of Networks between Order and Randomness , 2001 .

[3]  Gordon Bell,et al.  MyLifeBits: a personal database for everything , 2006, CACM.

[4]  Per Bak,et al.  Small Worlds: The Dynamics of Networks between Order and Randomness, by Duncan J. Watts , 2000 .

[5]  Alessandro Vespignani,et al.  Network Science , 2006 .

[6]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[7]  Sergey N. Dorogovtsev,et al.  Evolution of Networks: From Biological Nets to the Internet and WWW (Physics) , 2003 .

[8]  Rudolf Wille,et al.  A Triadic Approach to Formal Concept Analysis , 1995, ICCS.

[9]  John Riedl,et al.  Recommender systems in e-commerce , 1999, EC '99.

[10]  Donald J. McCubbrey,et al.  Management Information Systems for the Information Age , 1997 .

[11]  Anthony Jameson,et al.  User Modeling and User-Adapted Interaction , 2004, User Modeling and User-Adapted Interaction.

[12]  M. Buckland.  Emanuel Goldberg, electronic document retrieval, and Vannevar Bush's Memex , 1992 .

[13]  Gerd Stumme,et al.  A Finite State Model for On-Line Analytical Processing in Triadic Contexts , 2005, ICFCA.

[14]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[15]  David Bawden,et al.  Book Review: Evolution and Structure of the Internet: A Statistical Physics Approach. , 2006 .

[16]  S. Dongen.  A cluster algorithm for graphs , 2000 .

[17]  Michael J. Muller,et al.  Ethnographic study of collaborative knowledge work , 2006, IBM Syst. J..

[18]  Michael J. Pazzani,et al.  User Modeling for Adaptive News Access , 2000, User Modeling and User-Adapted Interaction.

[19]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[20]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[21]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[22]  Andreas Hotho,et al.  Information Retrieval in Folksonomies: Search and Ranking , 2006, ESWC.

[23]  Tony Hammond,et al.  Social Bookmarking Tools (I): A General Overview , 2005, D Lib Mag..

[24]  Jimeng Sun,et al.  Beyond streams and graphs: dynamic tensor analysis , 2006, KDD '06.

[25]  David Carmel,et al.  Trend detection through temporal link analysis , 2004, J. Assoc. Inf. Sci. Technol..

[26]  Andreas Hotho,et al.  Mining Association Rules in Folksonomies , 2006, Data Science and Classification.

[27]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[28]  Rudolf Wille,et al.  Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts , 2009, ICFCA.

[29]  Vannevar Bush,et al.  As we may think , 1945, INTR.

[30]  Stuart E. Middleton,et al.  Ontological user profiling in recommender systems , 2004, TOIS.

[31]  John Riedl,et al.  Recommender Systems: A GroupLens Perspective , 1998 .

[32]  Jie Wu,et al.  Small Worlds: The Dynamics of Networks between Order and Randomness , 2003 .

[33]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[34]  Tony Hammond,et al.  Social Bookmarking Tools (II): A Case Study - Connotea , 2005, D Lib Mag..