Thematic mapping - from unstructured documents to taxonomies
Proceedings of the eleventh international conference on Information and knowledge management
Graph Visualization and Navigation in Information Visualization: A Survey
IEEE Transactions on Visualization and Computer Graphics
Adaptive topological tree structure for document organisation and visualisation
Neural Networks - 2004 Special issue: New developments in self-organizing systems
The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data
IEEE Transactions on Neural Networks
Web content management by self-organization
IEEE Transactions on Neural Networks
Bringing taxonomic structure to large digital libraries
International Journal of Metadata, Semantics and Ontologies
Web feed clustering and tagging aggregator using topological tree-based self-organizing maps
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Creating topic hierarchies for large medical libraries
KR4HC'09 Proceedings of the 2009 AIME international conference on Knowledge Representation for Health-Care: data, Processes and Guidelines
| Hi-index | 0.00 |
In the knowledge economy taxonomy generation, information retrieval and portals in intelligent enterprises need to be dynamically adaptive to changes in their enterprise content. To remain competitive and efficient, this has to be done without exclusively relying on knowledge workers to update taxonomies or manually label documents. This paper briefly reviews existing visualisation methods used in presenting search results retrieved from a web search engine. A method, termed topological tree, that could be use to automatically organise large sets of documents retrieved from any type of search, is presented. The retrieved results, organised using an online version of the topological tree method, are compared to the visual representation of a web search engine that uses a document clustering algorithm. A discussion is made on the criterions of representing hierarchical relationships, having visual scalability, presenting underlying topics extracted from the document set, and providing a clear view of the connections between topics. The topological tree has been found to be a superior representation in all cases and well suited for organising web content.