Scaling personalized web search
WWW '03 Proceedings of the 12th international conference on World Wide Web
Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search
IEEE Transactions on Knowledge and Data Engineering
ACM Transactions on Internet Technology (TOIT)
IEEE Transactions on Knowledge and Data Engineering
SIAM Journal on Scientific Computing
Real-time automatic tag recommendation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
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
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Pairwise interaction tensor factorization for personalized tag recommendation
Proceedings of the third ACM international conference on Web search and data mining
Hybrid tag recommendation for social annotation systems
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Extending FolkRank with content data
Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web
Utilising document content for tag recommendation in folksonomies
Proceedings of the sixth ACM conference on Recommender systems
Fast Recommendation on Bibliographic Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Hi-index | 0.00 |
This paper looks inside FolkRank, one of the well-known folksonomy-based algorithms, to present its fundamental properties and promising possibilities for improving performance in tag recommendations. Moreover, we introduce a new way to compute a differential approach in FolkRank by representing it as a linear combination of the personalized PageRank vectors. By the linear combination, we present FolkRank's probabilistic interpretation that grasps how FolkRank works on a folksonomy graph in terms of the random surfer model. We also propose new FolkRank-like methods for tag recommendations to efficiently compute tags' rankings and thus reduce expensive computational cost of FolkRank. We show that the FolkRank approaches are feasible to recommend tags in real-time scenarios as well. The experimental evaluations show that the proposed methods provide fast tag recommendations with reasonable quality, as compared to FolkRank. Additionally, we discuss the diversity of the top n tags recommended by FolkRank and its variants.