A recommender system based on tag and time information for social tagging systems

Recently, social tagging has become increasingly prevalent on the Internet, which provides an effective way for users to organize, manage, share and search for various kinds of resources. These tagging systems offer lots of useful information, such as tag, an expression of user's preference towards a certain resource; time, a denotation of user's interests drift. As information explosion, it is necessary to recommend resources that a user might like. Since collaborative filtering (CF) is aimed to provide personalized services, how to integrate tag and time information in CF to provide better personalized recommendations for social tagging systems becomes a challenging task. In this paper, we investigate the importance and usefulness of tag and time information when predicting users' preference and examine how to exploit such information to build an effective resource-recommendation model. We design a recommender system to realize our computational approach. Also, we show empirically using data from a real-world dataset that tag and time information can well express users' taste and we also show that better performances can be achieved if such information is integrated into CF.

[1]  Nigel Shadbolt,et al.  A Study of User Profile Generation from Folksonomies , 2008, SWKM.

[2]  Hisham M. Haddad,et al.  Proceedings of the 2008 ACM Symposium on Applied Computing (SAC), Fortaleza, Ceara, Brazil, March 16-20, 2008 , 2008, SAC.

[3]  GeunSik Jo,et al.  Collaborative Tagging in Recommender Systems , 2007, Australian Conference on Artificial Intelligence.

[4]  Yuan Cheng,et al.  Model bloggers' interests based on forgetting mechanism , 2008, WWW.

[5]  Feng Boqin,et al.  Tag-based user modeling using formal concept analysis , 2008, 2008 8th IEEE International Conference on Computer and Information Technology.

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

[7]  Sooyoung Kim,et al.  Classification-based collaborative filtering using market basket data , 2005, Expert Syst. Appl..

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

[9]  Daniel Kifer,et al.  Context-aware citation recommendation , 2010, WWW '10.

[10]  Xue Li,et al.  Time weight collaborative filtering , 2005, CIKM '05.

[11]  John Riedl,et al.  Item-based collaborative filtering recommendation algorithms , 2001, WWW '01.

[12]  Ryszard S. Michalski,et al.  Selecting Examples for Partial Memory Learning , 2000, Machine Learning.

[13]  Licia Capra,et al.  kNN CF: a temporal social network , 2008, RecSys '08.

[14]  Jianchang Mao,et al.  Towards the Semantic Web: Collaborative Tag Suggestions , 2006 .

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

[16]  Alexander Tuzhilin,et al.  Using Context to Improve Predictive Modeling of Customers in Personalization Applications , 2008, IEEE Transactions on Knowledge and Data Engineering.

[17]  Philip S. Yu,et al.  A Framework for Projected Clustering of High Dimensional Data Streams , 2004, VLDB.

[18]  Young Park,et al.  A time-based approach to effective recommender systems using implicit feedback , 2008, Expert Syst. Appl..

[19]  Xin Li,et al.  Tag-based social interest discovery , 2008, WWW.

[20]  Bamshad Mobasher,et al.  Personalized recommendation in social tagging systems using hierarchical clustering , 2008, RecSys '08.

[21]  Young Park,et al.  An empirical study on effectiveness of temporal information as implicit ratings , 2009, Expert Syst. Appl..

[22]  George Karypis,et al.  Item-based top-N recommendation algorithms , 2004, TOIS.

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

[24]  Georgia Koutrika,et al.  Can social bookmarking improve web search? , 2008, WSDM '08.

[25]  J. Walther.  Computer-Mediated Communication , 1996 .

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

[27]  Nigel Shadbolt,et al.  Discovering and Modelling Multiple Interests of Users in Collaborative Tagging Systems , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[28]  Annie Chen,et al.  Context-Aware Collaborative Filtering System: Predicting the User's Preference in the Ubiquitous Computing Environment , 2005, LoCA.

[29]  Roelof van Zwol,et al.  Flickr tag recommendation based on collective knowledge , 2008, WWW.

[30]  Antal van den Bosch,et al.  Recommending scientific articles using citeulike , 2008, RecSys '08.

[31]  Pasquale Lops,et al.  Integrating tags in a semantic content-based recommender , 2008, RecSys '08.

[32]  Steve Cayzer,et al.  Learning User Profiles from Tagging Data and Leveraging them for Personal(ized) Information Access , 2007, WWW 2007.

[33]  Shinsuke Nakajima,et al.  Tag-Based Contextual Collaborative Filtering , 2007 .

[34]  Gediminas Adomavicius,et al.  Incorporating contextual information in recommender systems using a multidimensional approach , 2005, TOIS.

[35]  Adam Mathes,et al.  Folksonomies-Cooperative Classification and Communication Through Shared Metadata , 2004 .