Implementing agglomerative hierarchic clustering algorithms for use in document retrieval
Information Processing and Management: an International Journal
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Constant interaction-time scatter/gather browsing of very large document collections
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Reexamining the cluster hypothesis: scatter/gather on retrieval results
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Journal of Parallel and Distributed Computing
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Evaluating document clustering for interactive information retrieval
Proceedings of the tenth international conference on Information and knowledge management
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Link analysis for collaborative knowledge building
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Learning to match ontologies on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Document co-organization in an online knowledge community
CHI '04 Extended Abstracts on Human Factors in Computing Systems
Web taxonomy integration using support vector machines
Proceedings of the 13th international conference on World Wide Web
Collaborative filing in a document repository
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Searching and browsing text collections with large category hierarchies
CHI EA '97 CHI '97 Extended Abstracts on Human Factors in Computing Systems
ACM SIGMOD Record
Combining schema and instance information for integrating heterogeneous data sources
Data & Knowledge Engineering
Collaborative structuring: organizing document repositories effectively and efficiently
Communications of the ACM - Creating a science of games
Collaborative classification of growing collections with evolving facets
Proceedings of the eighteenth conference on Hypertext and hypermedia
ACM Computing Surveys (CSUR)
Design and natural science research on information technology
Decision Support Systems
Mining web navigations for intelligence
Decision Support Systems - Special issue: Intelligence and security informatics
Design science in information systems research
MIS Quarterly
A Clustering-Based Approach for Integrating Document-Category Hierarchies
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Understanding Web 2.0 service models: A knowledge-creating perspective
Information and Management
Design theory in practice: making design science research more transparent
DESRIST'11 Proceedings of the 6th international conference on Service-oriented perspectives in design science research
A semantic-based approach for searching and browsing tag spaces
Decision Support Systems
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Keeping large, growing document repositories organized is a critical challenge. For example, the security failure prior to the 9/11 tragedy was partly due to the ineffectiveness of organizing documents shared among various intelligence organizations. Drawing on the success of Web 2.0 and theories from knowledge management, we argue that a shared document repository with no central organizer may benefit from collective taxonomizing: allowing community members to categorize documents with local document hierarchies and systematically coalesce those local hierarchies into a global taxonomy. Using a design science approach, we develop and evaluate a hierarchy coalescing algorithm. Empirical and analytical evaluation shows promise.