The effectiveness of document neighboring in search enhancement
Information Processing and Management: an International Journal
The cluster hypothesis revisited
SIGIR '85 Proceedings of the 8th annual international ACM SIGIR conference on Research and development in information retrieval
Query-sensitive similarity measures for the calculation of interdocument relationships
Proceedings of the tenth international conference on Information and knowledge management
Information Retrieval
Evaluation of find-similar with simulation and network analysis
Evaluation of find-similar with simulation and network analysis
Do subtopic judgments reflect diversity?
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
The optimum clustering framework: implementing the cluster hypothesis
Information Retrieval
Exploring the cluster hypothesis, and cluster-based retrieval, over the web
Proceedings of the 21st ACM international conference on Information and knowledge management
Probabilistic co-relevance for query-sensitive similarity measurement in information retrieval
Information Processing and Management: an International Journal
The cluster hypothesis for entity oriented search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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We have found that the nearest neighbor (NN) test is an insufficient measure of the cluster hypothesis. The NN test is a local measure of the cluster hypothesis. Designers of new document-to-document similarity measures may incorrectly report effective clustering of relevant documents if they use the NN test alone. Utilizing a measure from network analysis, we present a new, global measure of the cluster hypothesis: normalized mean reciprocal distance. When used together with a local measure, such as the NN test, this new global measure allows researchers to better measure the cluster hypothesis.