Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
The Journal of Machine Learning Research
Ontology extraction and conceptual modeling for web information
Information modeling for internet applications
ICML '05 Proceedings of the 22nd international conference on Machine learning
Usage patterns of collaborative tagging systems
Journal of Information Science
Towards effective browsing of large scale social annotations
Proceedings of the 16th international conference on World Wide Web
Topic modeling with network regularization
Proceedings of the 17th international conference on World Wide Web
An unsupervised model for exploring hierarchical semantics from social annotations
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Towards automated georeferencing of Flickr photos
Proceedings of the 6th Workshop on Geographic Information Retrieval
Modeling the evolution of associated data
Data & Knowledge Engineering
Extraction of Places Related to Flickr Tags
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Towards a framework for trusting the automated learning of social ontologies
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
Combining multi-resolution evidence for georeferencing Flickr images
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
TagSorting: a tagging environment for collaboratively building ontologies
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Topic-based ranking in Folksonomy via probabilistic model
Artificial Intelligence Review
Ontology learning from text: A look back and into the future
ACM Computing Surveys (CSUR)
Personalized resource categorisation in folksonomies
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
Personalization in tag ontology learning for recommendation making
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services
Cross-lingual query expansion in multilingual folksonomies: A case study on Flickr
Knowledge-Based Systems
Learning personalized tag ontology from user tagging information
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Mining and recommending software features across multiple web repositories
Proceedings of the 5th Asia-Pacific Symposium on Internetware
Tag recommendation for open source software
Frontiers of Computer Science: Selected Publications from Chinese Universities
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A folksonomy refers to a collection of user-defined tags with which users describe contents published on the Web. With the flourish of Web 2.0, folksonomies have become an important mean to develop the Semantic Web. Because tags in folksonomies are authored freely, there is a need to understand the structure and semantics of these tags in various applications. In this paper, we propose a learning approach to create an ontology that captures the hierarchical semantic structure of folksonomies. Our experimental results on two different genres of real world data sets show that our method can effectively learn the ontology structure from the folksonomies.