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» Combined Data Mining Approach for Intrusion Detection
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EMNLP
2009
13 years 6 months ago
Classifier Combination for Contextual Idiom Detection Without Labelled Data
We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
Linlin Li, Caroline Sporleder
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
14 years 9 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
ICEIS
2008
IEEE
14 years 3 months ago
Next-Generation Misuse and Anomaly Prevention System
Abstract. Network Intrusion Detection Systems (NIDS) aim at preventing network attacks and unauthorised remote use of computers. More accurately, depending on the kind of attack it...
Pablo Garcia Bringas, Yoseba K. Penya
KDD
2012
ACM
235views Data Mining» more  KDD 2012»
11 years 11 months ago
A near-linear time approximation algorithm for angle-based outlier detection in high-dimensional data
Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional ...
Ninh Pham, Rasmus Pagh
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
14 years 6 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