Abstract
Recently, cluster-based retrieval has been successfully applied to improve retrieval effectiveness. The core part of cluster-based retrieval is inter-document similarities. Although inter-document similarities can be investigated independently of cluster-based retrieval and be further improved in various ways, their direct evaluation has not been seriously considered. Considering that there are many cluster-based retrieval methods, such a direct evaluation method can separate the work of inter-document similarities from the work of cluster-based retrieval. For this purpose, this paper revisits Voorhee’s nearest neighbor test as such a direct evaluation, by mainly focusing on whether or not the test is correlated to the retrieval effectiveness. Experimental results consistently verify the use of the nearest neighbor test. As a result, we conclude that the improvement of retrieval effectiveness can be well-predictable from direct evaluation, even without performing runs of cluster-based retrieval.
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© 2008 Springer-Verlag Berlin Heidelberg
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Na, SH., Kang, IS., Lee, JH. (2008). Revisit of Nearest Neighbor Test for Direct Evaluation of Inter-document Similarities. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_77
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DOI: https://doi.org/10.1007/978-3-540-78646-7_77
Publisher Name: Springer, Berlin, Heidelberg
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