Data Stream Classification by Using Stacked CARU Networks

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

RNN based networks have been widely used in various applications to obtain impressive performance, and CARU has more advantages in NLP tasks. However, the RNN exerts a great pressure on the CARU unit when a single layer is used. In this work, we propose to implement a multi-layer design, which can gradually extract the main features through multiple CARU units. The advantage of this is that it can consider part of speech and content. It allows each layer to perform its work clearly while alleviating long-term dependencies. Using seven popular data streams, the performance of multi-layer CARU is compared and evaluated with many state-of-the-art technologies. Experiments show that our design can improve the classification performance of various data sets. In addition, the design and implementation can be easily deployed in RNN based systems.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
EditorsHerwig Unger, Young-Kuk Kim, Eenjun Hwang, Sung-Bae Cho, Stephan Pareigis, Kyamakya Kyandoghere, Young-Guk Ha, Jinho Kim, Atsuyuki Morishima, Christian Wagner, Hyuk-Yoon Kwon, Yang-Sae Moon, Carson Leung
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages385-390
Number of pages6
ISBN (Electronic)9781665421973
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022 - Daegu, Korea, Republic of
Duration: 17 Jan 202220 Jan 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022

Conference

Conference2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
Country/TerritoryKorea, Republic of
CityDaegu
Period17/01/2220/01/22

Keywords

  • CARU
  • Classification
  • Multilayer
  • RNN

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