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REVISIT OF NEAREST NEIGHBOR TEST FOR DIRECT EVALUATION OF INTER-DOCUMENT SIMILARITIES SCIE SCOPUS

Title
REVISIT OF NEAREST NEIGHBOR TEST FOR DIRECT EVALUATION OF INTER-DOCUMENT SIMILARITIES
Authors
Na, S.-HKang, I.-SLee, J.-H.
Date Issued
2008-01
Publisher
SPRINGER
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.
URI
https://oasis.postech.ac.kr/handle/2014.oak/35957
DOI
10.1007/978-3-540-78646-7_77
ISSN
0302-9743
Article Type
Article
Citation
LECTURE NOTES IN COMPUTER SCIENCE, vol. 4956, page. 674 - 678, 2008-01
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이종혁LEE, JONG HYEOK
Grad. School of AI
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