Data cleaning: Overview and emerging challenges

X Chu, IF Ilyas, S Krishnan, J Wang - Proceedings of the 2016 …, 2016 - dl.acm.org
Detecting and repairing dirty data is one of the perennial challenges in data analytics, and
failure to do so can result in inaccurate analytics and unreliable decisions. Over the past few …

Distance-based outlier detection in data streams

L Tran, L Fan, C Shahabi - Proceedings of the VLDB Endowment, 2016 - dl.acm.org
Continuous outlier detection in data streams has important applications in fraud detection,
network security, and public health. The arrival and departure of data objects in a streaming …

Efficient and flexible algorithms for monitoring distance-based outliers over data streams

M Kontaki, A Gounaris, AN Papadopoulos, K Tsichlas… - Information systems, 2016 - Elsevier
Anomaly detection is considered an important data mining task, aiming at the discovery of
elements (known as outliers) that show significant diversion from the expected case. More …

NETS: extremely fast outlier detection from a data stream via set-based processing

S Yoon, JG Lee, BS Lee - Proceedings of the VLDB Endowment, 2019 - dl.acm.org
This paper addresses the problem of efficiently detecting outliers from a data stream as old
data points expire from and new data points enter the window incrementally. The proposed …

A method for the detection of fake reviews based on temporal features of reviews and comments

W Liu, J He, S Han, F Cai, Z Yang… - IEEE Engineering …, 2019 - ieeexplore.ieee.org
Online reviews and comments after product sales have become very important for making
buying and selling decisions. Fake reviews will affect such decisions due to deceptive …

DDoS detection and alleviation in IoT using SDN (SDIoT-DDoS-DA)

A Wani, S Revathi - Journal of The Institution of Engineers (India): Series B, 2020 - Springer
Abstract The Internet of Things (IoT) is an ever expanding discipline encompassing all orbits
of life, and its development has resulted in enormous benefits. IoT has made it possible for …

Unsupervised online detection and prediction of outliers in streams of sensor data

N Reunanen, T Räty, JJ Jokinen, T Hoyt… - International Journal of …, 2020 - Springer
Outliers are unexpected observations, which deviate from the majority of observations.
Outlier detection and prediction are challenging tasks, because outliers are rare by …

Designing a streaming algorithm for outlier detection in data mining—An incremental approach

K Yu, W Shi, N Santoro - Sensors, 2020 - mdpi.com
To design an algorithm for detecting outliers over streaming data has become an important
task in many common applications, arising in areas such as fraud detections, network …

Outlier Detection using Clustering Techniques–K-means and K-median

B Angelin, A Geetha - 2020 4th International Conference on …, 2020 - ieeexplore.ieee.org
Outlier detection in data mining helps to identify and dispose of irregular data objects from
the given dataset. In this work, various clustering and outlier techniques are initially …

Mining big data streams using business analytics tools: a bird's eye view on MOA and SAMOA

PM Arunkumar, S Kannimuthu - International Journal of …, 2020 - inderscienceonline.com
Big data evolves as the prominent field in modern computing era. Big data analytics and its
impact on extracting business intelligence is becoming indispensable for plethora of …