FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances Extended Abstract-Reference-Cited by-同舟云学术

FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances Extended Abstract

Published:2001 Issue: Volume: Page:101-110
ISSN:0302-9743
Container-title:Data Warehousing and Knowledge Discovery
language:
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Author:

Wyss Catharine,Giannella Chris,Robertson Edward

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/3-540-44801-2_11

Reference13 articles.

1. Agrawal, Rakesh; Mannila, Heikki; Srikant, Ramakrishnan; Toivonen, Hannu and Verkamo, A.I. “Fast Discovery of Association Rules.” Advances in KDD, AAA, Press, Menlo Park, CA, pg. 307–328, 1996.

2. Lect Notes Comput Sci;J. Demetrovics,1995

3. Eiter, Thomas and Gottlob, Goerg. “Identifying the Minimal Traversals of a Hypergraph and Related Problems.” SIAM Journal of Computing, vol. 24,no. 6, pg. 1278–1304, 1995.

4. Flach, Peter and Savnik, Iztok. “Database Dependency Discovery: a Machine Learning Approach.” AI Comm. vol. 12,no. 3, pg 139–160.

5. Gunopulos, Dimitrios; Khardon, Roni; Mannila, Heikki; and Toivonen, Hannu. “Data Mining, Hypergraph Traversals, and Machine Learning (extended abstract)”, PODS, 1997, pg 209–216.

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