short-paper

INforE: Interactive Cross-platform Analytics for Everyone

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

Pages 3389 - 3392

https://doi.org/10.1145/3340531.3417435

Published: 19 October 2020 Publication History

Abstract

We present INforE, a prototype supporting non-expert programmers in performing optimized, cross-platform, streaming analytics at scale. INforE offers: a) a new extension to the RapidMiner Studio for graphical design of Big streaming Data workflows, (b) a novel optimizer to instruct the execution of workflows across Big Data platforms and clusters, (c) a synopses data engine for interactivity at scale via the use of data summaries, (d) a distributed, online data mining and machine learning module. To our knowledge INforE is the first holistic approach in streaming settings. We demonstrate INforE in the fields of life science and financial data analysis.

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References

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Cited By

Kontaxakis ASacharidis DSimitsis AAbelló ANadal S(2024)HYPPO: Using Equivalences to Optimize Pipelines in Exploratory Machine Learning2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00024(221-234)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00024
Giatrakos NKougioumtzi EKontaxakis ADeligiannakis AKotidis YDemartini GZuccon GCulpepper JHuang ZTong H(2021)EasyFlinkCEPProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482094(3029-3033)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482094
Giatrakos NDeligiannakis ABereta KVodas MZissis DAlevizos EAkasiadis CArtikis A(2021)Processing Big Data in Motion: Core Components and System Architectures with Applications to the Maritime DomainTechnologies and Applications for Big Data Value10.1007/978-3-030-78307-5_22(497-518)Online publication date: 1-Jul-2021
https://doi.org/10.1007/978-3-030-78307-5_22

Index Terms

INforE: Interactive Cross-platform Analytics for Everyone
1. General and reference
  1. Cross-computing tools and techniques
2. Theory of computation
  1. Design and analysis of algorithms
    1. Streaming, sublinear and near linear time algorithms
  2. Models of computation
    1. Interactive computation

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cover image ACM Conferences

CIKM '20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management

October 2020

3619 pages

ISBN:9781450368599

DOI:10.1145/3340531

General Chairs:
Mathieu d'Aquin
DSI, Insight, NUI Galway, Ireland
,
Stefan Dietze
GESIS, Cologne, Germany, Heinrich-Heine-University Düsseldorf, Germany, L3S Research Center, Germany
,
Program Chairs:
Claudia Hauff
TU Delft, The Netherlands
,
Edward Curry
DSI, Insight, NUI Galway, Ireland
,
Philippe Cudre Mauroux
eXascale, University of Fribourg, Switzerland

Copyright © 2020 ACM.

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Published: 19 October 2020

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CIKM '20: The 29th ACM International Conference on Information and Knowledge Management

October 19 - 23, 2020

Virtual Event, Ireland

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Kontaxakis ASacharidis DSimitsis AAbelló ANadal S(2024)HYPPO: Using Equivalences to Optimize Pipelines in Exploratory Machine Learning2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00024(221-234)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDE60146.2024.00024
Giatrakos NKougioumtzi EKontaxakis ADeligiannakis AKotidis YDemartini GZuccon GCulpepper JHuang ZTong H(2021)EasyFlinkCEPProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482094(3029-3033)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482094
Giatrakos NDeligiannakis ABereta KVodas MZissis DAlevizos EAkasiadis CArtikis A(2021)Processing Big Data in Motion: Core Components and System Architectures with Applications to the Maritime DomainTechnologies and Applications for Big Data Value10.1007/978-3-030-78307-5_22(497-518)Online publication date: 1-Jul-2021
https://doi.org/10.1007/978-3-030-78307-5_22

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