The use of cluster hierarchies in hypertext information retrieval
HYPERTEXT '89 Proceedings of the second annual ACM conference on Hypertext
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
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
Scatter/gather browsing communicates the topic structure of a very large text collection
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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
Modern Information Retrieval
Parallelizing the buckshot algorithm for efficient document clustering
Proceedings of the eleventh international conference on Information and knowledge management
The effectiveness of query-specific hierarchic clustering in information retrieval
Information Processing and Management: an International Journal
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Document clustering via adaptive subspace iteration
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Incremental hierarchical clustering of text documents
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
QoS Browsing for Web Service Selection
ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
TIARA: a visual exploratory text analytic system
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Inducing word senses to improve web search result clustering
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Interactive schematic summaries for exploration of surveillance video
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Clustering web search results with maximum spanning trees
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
The optimum clustering framework: implementing the cluster hypothesis
Information Retrieval
Scatter/Gather browsing of web service QoS data
Future Generation Computer Systems
Interpretation and trust: designing model-driven visualizations for text analysis
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Cluster labeling for multilingual scatter/gather using comparable corpora
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
On the use of consensus clustering for incremental learning of topic hierarchies
SBIA'12 Proceedings of the 21st Brazilian conference on Advances in Artificial Intelligence
Studying the clustering paradox and scalability of search in highly distributed environments
ACM Transactions on Information Systems (TOIS)
Interactive search result clustering: a study of user behavior and retrieval effectiveness
Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries
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We proposed and implemented a novel clustering algorithm called LAIR2, which has constant running time average for on-the-fly Scatter/Gather browsing [4]. Our experiments showed that when running on a single processor, the LAIR2 on-line clustering algorithm was several hundred times faster than a parallel Buckshot algorithm running on multiple processors [11]. This paper reports on a study that examined the effectiveness of the LAIR2 algorithm in terms of clustering quality and its impact on retrieval performance. We conducted a user study on 24 subjects to evaluate on-the-fly LAIR2 clustering in Scatter/Gather search tasks by comparing its performance to the Buckshot algorithm, a classic method for Scatter/Gather browsing [4]. Results showed significant differences in terms of subjective perceptions of clustering quality. Subjects perceived that the LAIR2 algorithm produced significantly better quality clusters than the Buckshot method did. Subjects felt that it took less effort to complete the tasks with the LAIR2 system, which was more effective in helping them in the tasks. Interesting patterns also emerged from subjects' comments in the final open-ended questionnaire. We discuss implications and future research.