A Survey on Cluster Based Outlier Detection Techniques in Data Stream

No abstract is available for this paper.

• Publication year

  2016

• Venue

  International Journal of Data Mining Techniques and Applications

• Publication date

  2016-06-15

• Fields of study

  Computer Science

• Identifiers
  DOI 10.20894/IJDMTA.102.005.001.023
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Computer An Efficient Clustering Algorithm for Outlier Detection in Data Streams

  2017cited by this paper
• A Study of Clustering Based Algorithm for Outlier Detection in Data streams

  2015cited by this paper
• K-Medoids Clustering Using Partitioning Around Medoids for Performing Face Recognition

  2014cited by this paper
• Advanced Research in Computer

  2012cited by this paper
• Density-based Projected Clustering over High Dimensional Data Streams

  2012cited by this paper
• OUTLIER DETECTION FOR DYNAMIC DATA STREAMS USING WEIGHTED K-MEANS

  2011cited by this paper
• An Outlier Detection Method Based on Clustering

  2011cited by this paper
• K-means v/s K-medoids: A Comparative Study

  2011cited by this paper
• Nonparametric depth-based multivariate outlier identifiers, and masking robustness properties

  2010cited by this paper
• Efficient anomaly monitoring over moving object trajectory streams

  2009cited by this paper
• Outlier Detection with the Kernelized Spatial Depth Function

  2009cited by this paper
• Anomaly detection: A survey

  2009cited by this paper
• Efficient Clustering-Based Outlier Detection Algorithm for Dynamic Data Stream

  2008cited by this paper
• Density-based clustering for real-time stream data

  2007cited by this paper
• Density-Based Clustering over an Evolving Data Stream with Noise

  2006cited by this paper
• A Comparative Study for Outlier Detection Techniques in Data Mining

  2006cited by this paper
• Outlier Detection: Principles, Techniques and Applications

  2006cited by this paper
• Data mining for security

  2005cited by this paper
• A Framework for Projected Clustering of High Dimensional Data Streams

  2004influential reference
• Discovering cluster-based local outliers

  2003cited by this paper
• Data Mining: Concepts and Techniques

  2000influential reference
• On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms

  2000cited by this paper
• Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

  1998cited by this paper
• Algorithms for Mining Distance-Based Outliers in Large Datasets

  1998cited by this paper
• A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise

  1996influential reference
• On the generalized distance in statistics

  1936cited by this paper
• Noname manuscript No. (will be inserted by the editor) A Novel Approach to Noise Clustering for Outlier Detection

  year unknowncited by this paper

• PERFORMANCE ENHANCEMENT MODEL OF CLUSTERING TECHNIQUES FOR OUTLIER DETECTION

  2022cites this paper
• STUDY THE MODEL OF CLUSTERING TECHNIQUES FOR OUTLIER DETECTION

  2022cites this paper
• Indoor Wireless Multipaths Outlier Detection and Clustering

  2022cites this paper
• A Fast and Efficient Algorithm for Outlier Detection Over Data Streams

  2021cites this paper
• A Survey on Anomaly Detection Methods for System Log Data

  2019cites this paper
• An efficient and robust cluster based outlying points detection in multivariate data sets

  2018cites this paper
• A heuristic approach for observing outlying points in diabetes data set

  2017cites this paper