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Extended Boolean information retrieval
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PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
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OntoMiner: bootstrapping ontologies from overlapping domain specific web sites
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IV '04 Proceedings of the Information Visualisation, Eighth International Conference
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Taxonomy generation for text segments: A practical web-based approach
ACM Transactions on Information Systems (TOIS)
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ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
CP/CV: concept similarity mining without frequency information from domain describing taxonomies
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
CDIP: Collection-Driven, yet Individuality-Preserving Automated Blog Tagging
ICSC '07 Proceedings of the International Conference on Semantic Computing
Discovering Subsumption Hierarchies of Ontology Concepts from Text Corpora
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Ontology generation for large email collections
dg.o '08 Proceedings of the 2008 international conference on Digital government research
Using tagflake for condensing navigable tag hierarchies from tag clouds
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Towards the Automatic Construction of Conceptual Taxonomies
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Hive open research network platform
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Managing legal interpretation in regulatory compliance
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Law
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The use of tag clouds is common for presenting frequently occurring tags or keywords in a collection to the users. Most visualizations of tag clouds vary the sizes of the fonts to differentiate important tags from others. This, however, is sufficient neither to help the user explore and discover relationships between tags in a collection, nor to help track the changes in these relationships across time frames in dynamic collections. In this paper, we propose an alternative ''contextual-layout'' method, tag-flakes, for presenting tags or keywords that are associated with dynamically evolving textual content, like news streams. A TMine algorithm first maps tags onto a latent semantic space. However, instead of using this latent semantic space to simply cluster and index the documents (as commonly done in many existing schemes), TMine analyzes the relationships between tags in this semantic space and the resulting tag cloud is condensed into a hierarchy (or a tag-flake) in a way that captures contextual relationships between tags: descendant terms in the hierarchy occur within the context defined by the ancestor terms. This provides a mechanism for navigation within the tag space as well as for the contextual organization of the text documents. We use TMine in developing the tagFlake visualization system, which relies on TMine for organizing tags extracted from news collections in a hierarchical manner and supports navigation within the collection through these contextually laid-out tag clouds. tagFlake also helps users track topic developments and changes in the context in which certain keywords are used. Experimental evaluation results show the effectiveness of the proposed TMine method in capturing the semantic structures of collections.