Techniques for the measurement of clustering tendency in document retrieval systems
Journal of Information Science
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
A neural algorithm for document clustering
Information Processing and Management: an International Journal - Special issue on parallel processing and information retrieval
A self-organizing semantic map for information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Exploration of text collections with hierarchical feature maps
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Self-organizing maps
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Internet browsing and searching: user evaluations of category map and concept space techniques
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
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
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Extracting meaningful labels for WEBSOM text archives
Proceedings of the tenth international conference on Information and knowledge management
FOCI: flexible organizer for competitive intelligence
Proceedings of the tenth international conference on Information and knowledge management
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Modern Information Retrieval
Unsupervised document classification using sequential information maximization
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Document clustering with cluster refinement and model selection capabilities
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Information navigation on the web by clustering and summarizing query results
Information Processing and Management: an International Journal
Text Retrieval Using Self-Organized Document Maps
Neural Processing Letters
Hierarchical Growing Cell Structures: TreeGCS
IEEE Transactions on Knowledge and Data Engineering
Self-organizing map for clustering in the graph domain
Pattern Recognition Letters - In memory of Professor E.S. Gelsema
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Document Categorization and Retrieval Using Semantic Microfeatures and Growing Cell Structures
DEXA '01 Proceedings of the 12th International Workshop on Database and Expert Systems Applications
Self-Organising Maps for Hierarchical Tree View Document Clustering Using Contextual Information
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
Validation indices for graph clustering
Pattern Recognition Letters - Special issue: Graph-based representations in pattern recognition
Frequent term-based text clustering
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Integrating contextual information to enhance SOM-based text document clustering
Neural Networks - New developments in self-organizing maps
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
On the quality of ART1 text clustering
Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
Marginal median SOM for document organization and retrieval
Neural Networks
Self organization of a massive document collection
IEEE Transactions on Neural Networks
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Dynamic self-organizing maps with controlled growth for knowledge discovery
IEEE Transactions on Neural Networks
The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data
IEEE Transactions on Neural Networks
Large-scale data exploration with the hierarchically growing hyperbolic SOM
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Nonlinear Principal Manifolds --- Adaptive Hybrid Learning Approaches
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
Topological tree clustering of social network search results
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
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
Adaptive nonlinear manifolds and their applications to pattern recognition
Information Sciences: an International Journal
Binary tree time adaptive self-organizing map
Neurocomputing
Recurrent self-organising maps and local support vector machine models for exchange rate prediction
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Topological tree clustering of web search results
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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The self-organising map (SOM) is finding more and more applications in a wide range of fields, such as clustering, pattern recognition and visualisation. It has also been employed in knowledge management and information retrieval. We propose an alternative to existing 2-dimensional SOM based methods for document analysis. The method, termed Adaptive Topological Tree Structure (ATTS), generates a taxonomy of underlying topics from a set of unclassified, unstructured documents. The ATTS consists of a hierarchy of adaptive self-organising chains, each of which is validated independently using a proposed entropy-based Bayesian information criterion. A node meeting the expansion criterion spans a child chain, with reduced vocabulary and increased specialisation. The ATTS creates a topological tree of topics, which can be browsed like a content hierarchy and reflects the connections between related topics at each level. A review is also given on the existing neural network based methods for document clustering and organisation. Experimental results on real-world datasets using the proposed ATTS method are presented and compared with other approaches. The results demonstrate the advantages of the proposed validation criteria and the efficiency of the ATTS approach for document organisation, visualisation and search. It shows that the proposed methods not only improve the clustering results but also boost the retrieval.