Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Item-based top-N recommendation algorithms
ACM Transactions on Information Systems (TOIS)
Usage patterns of collaborative tagging systems
Journal of Information Science
Exploring social annotations for the semantic web
Proceedings of the 15th international conference on World Wide Web
Interest-based personalized search
ACM Transactions on Information Systems (TOIS)
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking enhance search in the web?
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Tag-based social interest discovery
Proceedings of the 17th international conference on World Wide Web
Exploring folksonomy for personalized search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Efficient top-k querying over social-tagging networks
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Social ranking: uncovering relevant content using tag-based recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
Tag recommendations in social bookmarking systems
AI Communications
Evaluating similarity measures for emergent semantics of social tagging
Proceedings of the 18th international conference on World wide web
Personalization of tagging systems
Information Processing and Management: an International Journal
Social Tagging in Query Expansion: A New Way for Personalized Web Search
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
Information Systems
Exploiting Social Tagging Profiles to Personalize Web Search
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
I tag, you tag: translating tags for advanced user models
Proceedings of the third ACM international conference on Web search and data mining
User Modeling and User-Adapted Interaction
Social tagging in recommender systems: a survey of the state-of-the-art and possible extensions
Artificial Intelligence Review
Web search personalization via social bookmarking and tagging
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
An elaborated model of social search
Information Processing and Management: an International Journal
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Personalizing web search with folksonomy-based user and document profiles
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Hi-index | 0.00 |
In recent years, social Web users have been overwhelmed by the huge numbers of social media available. Consequentially, users have trouble finding social media suited to their needs. To help such users retrieve useful social media content, we propose a new model of tag-based personalized searches to enhance not only retrieval accuracy but also retrieval coverage. By leveraging social tagging as a preference indicator, we build two models: (i) a latent tag preference model that reflects how a certain user has assigned tags similar to a given tag and (ii) a latent tag annotation model that captures how users have tagged a certain tag to resources similar to a given resource. We then seamlessly map the tags onto items, depending on an individual user's query, to find the most desirable content relevant to the user's needs. Experimental results demonstrate that the proposed method significantly outperforms the state-of-the art algorithms and show our method's feasibility for personalized searches in social media services.