Choosing the Right Lens: Finding What is Interesting in Data Mining-Reference-Cited by-同舟云学术

Choosing the Right Lens: Finding What is Interesting in Data Mining

Published:2007 Issue: Volume: Page:3-24
ISSN:1860-949X
Container-title:Quality Measures in Data Mining
language:
Short-container-title:

Author:

Geng Liqiang,Hamilton Howard J.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-44918-8_1.pdf

Reference52 articles.

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3. Baeza-Yates, R. and Ribeiro-Neto, B. Modern Information Retrieval. Addison Wesley, Boston, 1999.

4. Barnett, V., and Lewis, T. Outliers in Statistical Data. John Wiley and Sons, New York, 1994.

5. Bastide, Y., Pasquier, N., Taouil, R., Stumme, G., and Lakhal, L. Mining minimal non-redundant association rules using frequent closed itemsets. In Proceedings of the First International Conference on Computational Logic, pages 972-986, London, UK, 2000.

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