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KDD
2006
ACM
118views Data Mining» more  KDD 2006»
16 years 5 months ago
Mining for proposal reviewers: lessons learned at the national science foundation
In this paper, we discuss a prototype application deployed at the U.S. National Science Foundation for assisting program directors in identifying reviewers for proposals. The appl...
Seth Hettich, Michael J. Pazzani
ICDM
2006
IEEE
149views Data Mining» more  ICDM 2006»
15 years 11 months ago
Pattern Mining in Frequent Dynamic Subgraphs
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...
DAWAK
1999
Springer
15 years 9 months ago
Mining Interval Time Series
Data mining can be used to extensively automate the data analysis process. Techniques for mining interval time series, however, have not been considered. Such time series are commo...
Roy Villafane, Kien A. Hua, Duc A. Tran, Basab Mau...
KDD
2005
ACM
125views Data Mining» more  KDD 2005»
16 years 5 months ago
Email data cleaning
Addressed in this paper is the issue of `email data cleaning' for text mining. Many text mining applications need take emails as input. Email data is usually noisy and thus i...
Jie Tang, Hang Li, Yunbo Cao, ZhaoHui Tang
KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 9 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang