The Collaborative Search by Tag-Based User Profile in Social Media

Recently, we have witnessed the popularity and proliferation of social media applications (e.g., Delicious, Flickr, and YouTube) in the web 2.0 era. The rapid growth of user-generated data results in the problem of information overload to users. Facing such a tremendous volume of data, it is a big challenge to assist the users to find their desired data. To attack this critical problem, we propose the collaborative search approach in this paper. The core idea is that similar users may have common interests so as to help users to find their demanded data. Similar research has been conducted on the user log analysis in web search. However, the rapid growth and change of user-generated data in social media require us to discover a brand-new approach to address the unsolved issues (e.g., how to profile users, how to measure the similar users, and how to depict user-generated resources) rather than adopting existing method from web search. Therefore, we investigate various metrics to identify the similar users (user community). Moreover, we conduct the experiment on two real-life data sets by comparing the Collaborative method with the latest baselines. The empirical results show the effectiveness of the proposed approach and validate our observations.

[1]  Yuxin Mao,et al.  A Source-Initiated On-Demand Routing Algorithm Based on the Thorup-Zwick Theory for Mobile Wireless Sensor Networks , 2013, TheScientificWorldJournal.

[2]  Virgílio A. F. Almeida,et al.  A community-aware search engine , 2004, WWW '04.

[3]  Barry Smyth,et al.  HeyStaks: a real-world deployment of social search , 2012, RecSys '12.

[4]  Haoran Xie,et al.  Context-Aware Personalized Search Based on User and Resource Profiles in Folksonomies , 2012, APWeb.

[5]  Yong Yu,et al.  Exploring social annotations for the semantic web , 2006, WWW '06.

[6]  Juan-Zi Li,et al.  Typicality-Based Collaborative Filtering Recommendation , 2014, IEEE Transactions on Knowledge and Data Engineering.

[7]  Christoph Meinel,et al.  Web Search Personalization Via Social Bookmarking and Tagging , 2007, ISWC/ASWC.

[8]  Yuxin Mao,et al.  Cooperation Dynamics on Collaborative Social Networks of Heterogeneous Population , 2013, IEEE Journal on Selected Areas in Communications.

[9]  Qiang Yang,et al.  User language model for collaborative personalized search , 2009, TOIS.

[10]  Ryen W. White,et al.  Predicting user interests from contextual information , 2009, SIGIR.

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

[12]  Joemon M. Jose,et al.  Personalizing Web Search with Folksonomy-Based User and Document Profiles , 2010, ECIR.

[13]  Yong Yu,et al.  Exploring folksonomy for personalized search , 2008, SIGIR '08.

[14]  Y. Mass,et al.  Folksonomy-Based Term Extraction for Word Cloud Generation , 2011, TIST.

[15]  Kotagiri Ramamohanarao,et al.  Mining web multi-resolution community-based popularity for information retrieval , 2007, CIKM '07.

[16]  Zhiming Cui,et al.  A Collaborative Recommend Algorithm Based on Bipartite Community , 2014, TheScientificWorldJournal.

[17]  Haoran Xie,et al.  Community-Aware Resource Profiling for Personalized Search in Folksonomy , 2012, Journal of Computer Science and Technology.

[18]  Yueshen Xu,et al.  Social Network Supported Process Recommender System , 2014, TheScientificWorldJournal.

[19]  Barry Smyth,et al.  Social summarization in collaborative web search , 2010, Inf. Process. Manag..

[20]  Meredith Ringel Morris,et al.  Search on surfaces: Exploring the potential of interactive tabletops for collaborative search tasks , 2010, Inf. Process. Manag..

[21]  Meredith Ringel Morris,et al.  Discovering and using groups to improve personalized search , 2009, WSDM '09.

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

[23]  Barry Smyth,et al.  Social and collaborative web search: an evaluation study , 2011, IUI '11.

[24]  Wolfgang Nejdl,et al.  Can all tags be used for search? , 2008, CIKM '08.

[25]  Chunhua Ju,et al.  A New Collaborative Recommendation Approach Based on Users Clustering Using Artificial Bee Colony Algorithm , 2013, TheScientificWorldJournal.

[26]  Xiangfeng Luo,et al.  Measuring Semantic Relatedness between Flickr Images: From a Social Tag Based View , 2014, TheScientificWorldJournal.

[27]  M. Asadpour,et al.  A Supervised Approach to Predict the Hierarchical Structure of Conversation Threads for Comments , 2014, TheScientificWorldJournal.

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

[29]  Yi Cai,et al.  Personalized search by tag-based user profile and resource profile in collaborative tagging systems , 2010, CIKM.

[30]  Rui Li,et al.  Survey on social tagging techniques , 2010, SKDD.

[31]  Ruoming Jin,et al.  A Topic Modeling Approach and Its Integration into the Random Walk Framework for Academic Search , 2008, 2008 Eighth IEEE International Conference on Data Mining.

[32]  John Yen,et al.  Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model , 2007, AAAI.

[33]  Barry Smyth,et al.  A Community-Based Approach to Personalizing Web Search , 2007, Computer.