Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques
Data mining: concepts and techniques
Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Two-phase clustering process for outliers detection
Pattern Recognition Letters
Mining top-n local outliers in large databases
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Modern Information Retrieval
Findout: finding outliers in very large datasets
Knowledge and Information Systems
Algorithms for Mining Distance-Based Outliers in Large Datasets
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Distance-based outliers: algorithms and applications
The VLDB Journal — The International Journal on Very Large Data Bases
Discovering cluster-based local outliers
Pattern Recognition Letters
Detecting pattern-based outliers
Pattern Recognition Letters
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Outlier Mining in Large High-Dimensional Data Sets
IEEE Transactions on Knowledge and Data Engineering
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Improving Mining of Medical Data by Outliers Prediction
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Distance-Based Detection and Prediction of Outliers
IEEE Transactions on Knowledge and Data Engineering
Fast Distributed Outlier Detection in Mixed-Attribute Data Sets
Data Mining and Knowledge Discovery
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Knowledge and Information Systems
From outliers to prototypes: Ordering data
Neurocomputing
LDBOD: A novel local distribution based outlier detector
Pattern Recognition Letters
Fast mining of distance-based outliers in high-dimensional datasets
Data Mining and Knowledge Discovery
Outlier identification and market segmentation using kernel-based clustering techniques
Expert Systems with Applications: An International Journal
Some issues about outlier detection in rough set theory
Expert Systems with Applications: An International Journal
Projected outlier detection in high-dimensional mixed-attributes data set
Expert Systems with Applications: An International Journal
Inlier-Based Outlier Detection via Direct Density Ratio Estimation
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Cell-based outlier detection algorithm: a fast outlier detection algorithm for large datasets
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
A nonparametric outlier detection for effectively discovering top-n outliers from engineering data
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Ranking outliers using symmetric neighborhood relationship
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Algorithms for detecting outliers via clustering and ranks
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
| Hi-index | 12.05 |
This paper proposes a density-similarity-neighbor-based outlier mining algorithm for the data preprocess of data mining technique. First, the concept of k-density of an object is presented and the similar density series (SDS) of the object is established based on the changes of the k-density and the neighbors k-densities of the object. Second, the average series cost (ASC) of the object is obtained based on the weighted sum of the distance between the two adjacent objects in SDS of the object. Finally, the density-similarity-neighbor-based outlier factor (DSNOF) of the object is calculated by using both the ASC of the object and the ASC of k-distance neighbors of the object, and the degree of the object being an outlier is indicated by the DSNOF. The experiments are performed on synthetic and real datasets to evaluate the effectiveness and the performance of the proposed algorithm. The experiments results verify that the proposed algorithm has higher quality of outlier mining and do not increase the algorithm complexity.