On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
A study of smoothing methods for language models applied to Ad Hoc information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Investigating the relationship between language model perplexity and IR precision-recall measures
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Probabilistic author-topic models for information discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
The author-topic model for authors and documents
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
AutoTag: a collaborative approach to automated tag assignment for weblog posts
Proceedings of the 15th international conference on World Wide Web
LDA-based document models for ad-hoc retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
ArnetMiner: extraction and mining of academic social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Tag Recommendations in Folksonomies
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A method to predict social annotations
Proceedings of the 17th ACM conference on Information and knowledge management
Collaborative filtering for orkut communities: discovery of user latent behavior
Proceedings of the 18th international conference on World wide web
A Generalized Topic Modeling Approach for Maven Search
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Context-oriented web video tag recommendation
Proceedings of the 19th international conference on World wide web
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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Tag recommendation for new resources is one of the most important issues discussed recently.Many existing approaches ignore text semantics and can not recommend new tags which are not in the training dataset (e.g., FolkRank). Some exceptional semantic approaches use a probabilistic latent semantic method to recommend tags in terms of topic knowledge (e.g., ACT model). However, they do not perform well because many entities in these models result in much noise. In this paper, we propose hybrid approaches in folksonomy to challenge these problems. Hybrid approaches are combination of Language Model (LM) for keyword based approach and Latent Dirichlet Allocation (LDA), Tag-Topic (TT) model and User-Tag-Topic (UTT) model for topic based approaches. Our approaches can recommend meaningful tags and can be used to discover resource implicit correlations. Experimental results on Bibsonomy dataset show that LM performs better than all other hybrid and non-hybrid approaches. Also the hybrid approaches with less number of entities (e.g., LDA with only one entity) perform better than those approaches having more entities (e.g., UTT with three entities) for tag recommendation task.