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KDD
1995
ACM
129views Data Mining» more  KDD 1995»
15 years 28 days ago
Feature Extraction for Massive Data Mining
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
V. Seshadri, Raguram Sasisekharan, Sholom M. Weiss
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 28 days ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
KDD
1995
ACM
67views Data Mining» more  KDD 1995»
15 years 28 days ago
A Perspective on Databases and Data Mining
We discuss the use of database met hods for data mining. Recently impressive results have been achieved for some data mining problems using highly specialized and clever data stru...
Marcel Holsheimer, Martin L. Kersten, Heikki Manni...
KDD
1995
ACM
167views Data Mining» more  KDD 1995»
15 years 28 days ago
Efficient Algorithms for Attribute-Oriented Induction
Data mining or knowledge discovery in databasesis the search for relationships and global patterns that exist but are hidden in large databases.Many different methodshave been pro...
Hoi-Yee Hwang, Ada Wai-Chee Fu
KDD
1997
ACM
169views Data Mining» more  KDD 1997»
15 years 1 months ago
Learning to Extract Text-Based Information from the World Wide Web
Thereis a wealthof informationto be minedfromnarrative text on the WorldWideWeb.Unfortunately, standard natural language processing (NLP)extraction techniques expect full, grammat...
Stephen Soderland