Amanote Research

Amanote Research

    RegisterSign In

A Novel Framework for Context-Aware Outlier Detection in Big Data Streams

Journal of Digital Information Management - India
doi 10.6025/jdim/2018/16/5/213-222
Full Text
Open PDF
Abstract

Available in full text

Categories
Information SystemsManagement Information SystemsLibraryInformation Sciences
Date

October 1, 2018

Authors
Hussien AhmadSalah Dowaji
Publisher

Digital Information Research Foundation


Related search

A Hybrid Clustering Algorithm for Outlier Detection in Data Streams

International Journal of Grid and Distributed Computing
Computer Science
2016English

OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2012English

Hybrid Network-On-Chip: An Application-Aware Framework for Big Data

Complexity
MultidisciplinaryComputer Science
2018English

A Framework for Mobile, Context-Aware Applications

2009English

Outlier Detection for High-Dimensional Data

Biometrika
StatisticsProbabilityUncertaintyApplied MathematicsBiological SciencesAgriculturalMathematics
2015English

Object Detection for Big Data||Object Detection for Big Data

English

A Resource Oriented Framework for Context-Aware Enterprise Applications

2011English

Elgar Framework: Context-Aware Service Orchestration With Data Petri Net

2017English

Prototyping a Context-Aware Framework for Pervasive Entertainment Applications

2009English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy