The effectiveness and efficiency of agglomerative hierarchic clustering in document retrieval
The effectiveness and efficiency of agglomerative hierarchic clustering in document retrieval
Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Evaluating document clustering for interactive information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Topic detection and tracking evaluation overview
Topic detection and tracking
Corpora for topic detection and tracking
Topic detection and tracking
Explorations within topic tracking and detection
Topic detection and tracking
Event threading within news topics
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Scalable hierarchical topic detection: exploring a sample based approach
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Navigation behavior models for link structure optimization
User Modeling and User-Adapted Interaction
International Journal of Business Intelligence and Data Mining
Timeline Analysis of Web News Events
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Recovery Rate of Clustering Algorithms
PSIVT '09 Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology
Improving the dynamic hierarchical compact clustering algorithm by using feature selection
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Following the social media: aspect evolution of online discussion
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Event detection with spatial latent Dirichlet allocation
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Clustering-Based searching and navigation in an online news source
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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The Topic Detection and Tracking (TDT) evaluation program has included a "cluster detection" task since its inception in 1996. Systems were required to process a stream of broadcast news stories and partition them into non-overlapping clusters. A system's effectiveness was measured by comparing the generated clusters to "truth" clusters created by human annotators. Starting in 2003, TDT is moving to a more realistic model that permits overlapping clusters (stories may be on more than one topic) and encourages the creation of a hierarchy to structure the relationships between clusters (topics). We explore a range of possible evaluation models for this modified TDT clustering task to understand the best approach for mapping between the human-generated "truth" clusters and a much richer hierarchical structure. We demonstrate that some obvious evaluation techniques fail for degenerate cases. For a few others we attempt to develop an intuitive sense of what the evaluation numbers mean. We settle on some approaches that incorporate a strong balance between cluster errors (misses and false alarms) and the distance it takes to travel between stories within the hierarchy.