YoojuShin / MDUAL

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

MDUAL

Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries

This is the implementation of the paper published in SIGMOD 2021 [Paper] [Slide] [Poster] [Video]

1. Overview

Real-time outlier detection from a data stream has become increasingly important in the current hyperconnected world. This paper focuses on an important yet unaddressed challenge in continuous outlier detection: the multiplicity and dynamicity of queries. This challenge arises from various contexts of outliers evolving over time, but the state-of-the-art algorithms cannot handle the challenge effectively, as they can only process a fixed set of outlier detection queries for each data point separately. In this paper, we propose a novel algorithm, abbreviated as MDUAL, based on a new idea called duality-based unified processing. The underlying rationale is to exploit the duality of data and queries so that a group of similar data points are processed together by a group of similar queries incrementally. Two main techniques embodying the idea, data-query grouping and prioritized group processing, are employed. Comprehensive experiments showed that MDUAL runs 216 to 221 times faster while consuming 11 to 13 times less memory than the state-of-the-art algorithms through its efficient and effective handling of the multiplicity–dynamicity challenge.

2. Data Sets

Name # data points # Dim Size Link
STK 1.05M 1 7.57MB link
TAO 0.58M 3 10.7MB link
HPC 1M 7 28.4MB link
GAS 0.93M 10 70.7MB link
EM 1M 16 119MB link
FC 1M 55 72.2MB link

3. Configuration

MDUAL algorithm was implemented in JAVA and run on JDK 1.8.0_252.

  • Edit test/testLoad.java to set experiment parameters (dataset, num of queries, change rate, repeat num, etc.)
  • Compile and run
cd ~/MDUAL/src
javac test/testLoad.java
java test.testLoad
  • Example output
Dataset Queryset ChgQRatio Time AvgMem PeakMem #Out #OutQ   
STK STK_Q10 0.2 2.42 3.3 13.5 5 10  

4. Citation

@inproceedings{Yoon2021MDUAL,
  title={Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries},
  author={Yoon, Susik and Shin, Yooju and Lee, Jae-Gil and Lee, Byung Suk},
  booktitle={Proceedings of the 2021 ACM SIGMOD International Conference on Management of Data},
  year={2021}
}

About

License:Apache License 2.0


Languages

Language:Java 100.0%