BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A procedure for the detection of multivariate outliers
Computational Statistics & Data Analysis
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient algorithms for mining outliers from large data sets
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining and Knowledge Discovery
An Efficient Approximation Scheme for Data Mining Tasks
Proceedings of the 17th International Conference on Data Engineering
Algorithms for Mining Distance-Based Outliers in Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining the Knowledge Mine: The Hot Spots Methodology for Mining Large Real World Databases
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
The Integrated Delivery of Large-Scale Data Mining: The ACSys Data Mining Project
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
Distance-based outliers: algorithms and applications
The VLDB Journal — The International Journal on Very Large Data Bases
A unified approach for mining outliers
CASCON '97 Proceedings of the 1997 conference of the Centre for Advanced Studies on Collaborative research
Discovering cluster-based local outliers
Pattern Recognition Letters
Outlier Detection Algorithms in Data Mining Systems
Programming and Computing Software
Feature bagging for outlier detection
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A clustering-based method for unsupervised intrusion detections
Pattern Recognition Letters
Detecting outliers in interval data
Proceedings of the 44th annual Southeast regional conference
CURIO: a fast outlier and outlier cluster detection algorithm for large datasets
AIDM '07 Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining - Volume 84
Local peculiarity factor and its application in outlier detection
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A New Approach to Outlier Detection
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Outlier Detection with Kernel Density Functions
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Outlier Detection Based on Granular Computing
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Some issues about outlier detection in rough set theory
Expert Systems with Applications: An International Journal
ACM Computing Surveys (CSUR)
Outlier detection based on rough sets theory
Intelligent Data Analysis
A comprehensive survey of numeric and symbolic outlier mining techniques
Intelligent Data Analysis
A Predictive Analysis on Medical Data Based on Outlier Detection Method Using Non-Reduct Computation
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
A fast outlier detection strategy for distributed high-dimensional data sets with mixed attributes
Data Mining and Knowledge Discovery
Detecting unusual pattern with labeled data in two-stage
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Framework of clustering-based outlier detection
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
An information entropy-based approach to outlier detection in rough sets
Expert Systems with Applications: An International Journal
A resistant learning procedure for coping with outliers
Annals of Mathematics and Artificial Intelligence
Neighborhood outlier detection
Expert Systems with Applications: An International Journal
Robust data clustering by learning multi-metric Lq-norm distances
Expert Systems with Applications: An International Journal
A hybrid approach to outlier detection based on boundary region
Pattern Recognition Letters
A fast greedy algorithm for outlier mining
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
A unified subspace outlier ensemble framework for outlier detection
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
Outlier detection based on rough membership function
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
An optimization model for outlier detection in categorical data
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Assessing the quality and cleaning of a software project dataset: an experience report
EASE'06 Proceedings of the 10th international conference on Evaluation and Assessment in Software Engineering
Robust neural network for novelty detection on data streams
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Video synchronization as one-class learning
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Enhancing one-class support vector machines for unsupervised anomaly detection
Proceedings of the ACM SIGKDD Workshop on Outlier Detection and Description
Review: A review of novelty detection
Signal Processing
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We consider the problem of finding outliers in large multivariate databases. Outlier detection can be applied during the data cleansing process of data mining to identify problems with the data itself, and to fraud detection where groups of outliers are often of particular interest. We use replicator neural networks (RNNs) to provide a measure of the outlyingness of data records. The performance of the RNNs is assessed using a ranked score measure. The effectiveness of the RNNs for outlier detection is demonstrated on two publicly available databases.