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» Mining Several Data Bases with an Ensemble of Classifiers
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EMNLP
2010
13 years 5 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
SIGSOFT
2007
ACM
14 years 8 months ago
Training on errors experiment to detect fault-prone software modules by spam filter
The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics...
Osamu Mizuno, Tohru Kikuno
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
14 years 8 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
ADC
2007
Springer
145views Database» more  ADC 2007»
14 years 1 months ago
The Privacy of k-NN Retrieval for Horizontal Partitioned Data -- New Methods and Applications
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
Artak Amirbekyan, Vladimir Estivill-Castro
INCDM
2010
Springer
152views Data Mining» more  INCDM 2010»
13 years 11 months ago
Spam Email Filtering Using Network-Level Properties
Abstract. Spam is serious problem that affects email users (e.g. phishing attacks, viruses and time spent reading unwanted messages). We propose a novel spam email filtering appr...
Paulo Cortez, André Correia, Pedro Sousa, M...