An algorithm for suffix stripping
Readings in information retrieval
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Extracting significant time varying features from text
Proceedings of the eighth international conference on Information and knowledge management
Co-clustering documents and words using bipartite spectral graph partitioning
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Class-Driven Statistical Discretization of Continuous Attributes (Extended Abstract)
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Introduction to topic detection and tracking
Topic detection and tracking
Verbs semantics and lexical selection
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Proceedings of the 15th international conference on World Wide Web
cloudalicious: folksonomy over time
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Fighting Spam on Social Web Sites: A Survey of Approaches and Future Challenges
IEEE Internet Computing
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Time-Aware Web Users' Clustering
IEEE Transactions on Knowledge and Data Engineering
Integrating Folksonomies with the Semantic Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Discovering Trends in Collaborative Tagging Systems
PAISI, PACCF and SOCO '08 Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics
Correlating Time-Related Data Sources with Co-clustering
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
Co-Clustering Tags and Social Data Sources
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Personalized recommendation in social tagging systems using hierarchical clustering
Proceedings of the 2008 ACM conference on Recommender systems
Clustering of Social Tagging System Users: A Topic and Time Based Approach
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Spectral Clustering in Social-Tagging Systems
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Learning similarity metrics for event identification in social media
Proceedings of the third ACM international conference on Web search and data mining
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
Trend detection in folksonomies
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
Discretization of multidimensional web data for informative dense regions discovery
CIS'04 Proceedings of the First international conference on Computational and Information Science
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Tag recommendation by machine learning with textual and social features
Journal of Intelligent Information Systems
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The common ground behind most approaches that analyze social tagging systems is addressing the information challenge that emerges from the massive activity of millions of users who interact and share resources and/or metadata online. However, lack of any time-related data in the analysis process implicitly denies much of the dynamic nature of social tagging activity. In this paper we claim that holding a temporal dimension, allows for tracking macroscopic and microscopic users' interests, detecting emerging trends and recognizing events. To this end, we propose a time-aware co-clustering approach for acquiring semantic and temporal patterns out of the tagging activity. The resulted clusters contain both users and tags of similar patterns over time, and reveal non-obvious or "hidden" relations among users and topics of their common interest. Zoom in & out views serve as visualization methods on different aspects of the clusters' structure, in order to evaluate the efficiency of the approach.