Recent trends in hierarchic document clustering: a critical review
Information Processing and Management: an International Journal
Comparison of hierarchic agglomerative clustering methods for document retrieval
The Computer Journal
An investigation of document structures
Information Processing and Management: an International Journal
Concepts and effectiveness of the cover-coefficient-based clustering methodology for text databases
ACM Transactions on Database Systems (TODS)
On term selection for query expansion
Journal of Documentation
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th 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
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
Journal of the American Society for Information Science - Special issue: relevance research
The relevance of recall and precision in user evaluation
Journal of the American Society for Information Science - Special issue: relevance research
Journal of the American Society for Information Science - Special topic issue on the history of documentation and information science: part II
Information Retrieval Experiment
Information Retrieval Experiment
Information Retrieval
Cluster generation and cluster labelling for web snippets: a fast and accurate hierarchical solution
SPIRE'06 Proceedings of the 13th international conference on String Processing and Information Retrieval
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Users are known to experience difficulties in dealing with information retrieval search outputs, especially if those outputs are above a certain size. It has been argued by several researchers that search output clustering can help users in their interaction with IR systems in some retrieval situations, providing them with an overview of their results by exploiting the topicality information that resides in the output but has not been used at the retrieval stage. This overview might enable them to find relevant documents more easily by focusing on the most promising clusters, or to use the clusters as a starting-point for query refinement or expansion. In this paper, the results of experiments carried out to assess the viability of clustering as a search output presentation method are reported and discussed.