Finding Data Broadness Via Generalized Nearest Neighbors-Reference-Cited by-同舟云学术

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Finding Data Broadness Via Generalized Nearest Neighbors

Published:2006 Issue: Volume: Page:645-663
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Venkateswaran Jayendra,Kahveci Tamer,Camoglu Orhan

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11687238_39.pdf

Reference22 articles.

1. Albers, S.: Competitive Online Algorithms. Technical Report LS-96-2, brics (September 1996)

2. Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: International Conference on Management of Data (SIGMOD), pp. 322–331 (1990)

3. Berchtold, S., Ertl, B., Keim, D.A., Kriegel, H.-P., Seidl, T.: Fast Nearest Neighbor Search in High-dimensional Space. In: International Conference on Data Engineering (ICDE), pp. 209–218 (1998)

4. Lecture Notes in Computer Science;K. Beyer,1998

5. Böhm, C., Krebs, F.: The k-Nearest Neighbour Join: Turbo Charging the KDD Process. Knowledge and Information Systems (KAIS) 6(6) (2004)

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1. Towards Evaluating GRASIM for Ontology-Based Data Matching;On the Move to Meaningful Internet Systems, OTM 2010;2010

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