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» Learning Relational Concepts with Decision Trees
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ADMA
2005
Springer
157views Data Mining» more  ADMA 2005»
14 years 1 months ago
Learning k-Nearest Neighbor Naive Bayes for Ranking
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
Liangxiao Jiang, Harry Zhang, Jiang Su
IADIS
2004
13 years 9 months ago
Constructing Scorm Compliant Course Based on High Level Petri Nets
With rapid development of the Internet, e-learning system has become more and more popular. Currently, to solve the issue of sharing and reusing of teaching materials in different...
Jun-Ming Su, Shian-Shyong Tseng, Chia-Yu Chen, Jui...
DATAMINE
1999
108views more  DATAMINE 1999»
13 years 7 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
WWW
2009
ACM
14 years 8 months ago
Predicting click through rate for job listings
Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "p...
Manish S. Gupta
GIS
1992
ACM
13 years 11 months ago
Machine Induction of Geospatial Knowledge
Machine learning techniques such as tree induction have become accepted tools for developing generalisations of large data sets, typically for use with production rule systems in p...
Peter A. Whigham, Robert I. McKay, J. R. Davis