research-article

Distributed data integration and mining

Authors:

Viet Tran,

Ondrej Habala,

Branislav Simo,

Ladislav HluchyAuthors Info & Claims

iiWAS '11: Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services

Pages 435 - 438

https://doi.org/10.1145/2095536.2095624

Published: 05 December 2011 Publication History

Get Access

Abstract

In this paper, we describe the platform for distributed data integration and mining developed within ADMIRE project. Data are processed as streams by processing elements which are connected together into workflows. The workflows will be managed by distributed gateways which will optimize the workflow execution according to data locality and availability.

References

[1]

EU FP7 ICT project: Advanced Data Mining and Integration Research for Europe (ADMIRE), 2008--2011. Grant agreement no. 215024. Accessed March 2011. http://www.admire-project.eu

Google Scholar

[2]

Atkinson, M., Brezany, P., Krause, A., van Hemert, J., Janciak, I., Yaikhom, G.: DISPEL: Grammar and Concrete Syntax, version 1.0.The ADMIRE Project, February 2010. Accessed March 2011. http://www. admire-project.eu/docs/ADMIRE-D1.7-research-prototypes.pdf

Google Scholar

[3]

Ostrowski, R., Baxter, R.: ADMIRE Platfor Release 3 (ADMIRE D3.4). The ADMIRE Project, February 2010. http://www.admireproject.eu/docs/ADMIRE-D3.4-description.pdf (Accessed March 2011).

Google Scholar

[4]

Jackson, M., Antonioletti, M., Dobrzelecki, B., Chue Hong, N.: Distributed data management with OGSA-DAI. In: Fiore, S. and Aloisio, G. (eds.): Grid and Cloud Database Management. Springer Verlag 2011, to appear.

Google Scholar

[5]

Mouat, A., Janciak, I., Simo, B., Jarka, M., Baxter, R.: Tools Development Progress Report. ADMIRE project report. Accessed March 2011.

Google Scholar

[6]

Shearer, C: The CRISP-DM Model: The New Blueprint for Data Mining. Journal of Data Warehousing, 2000, Vol. 5, No. 4., pp.13--22.

Google Scholar

[7]

Des Rivieres, J. and Wiegand, J.: Eclipse: a platform for integrating development tools. IBM Syst. J., April 2004,

Digital Library

Google Scholar

[8]

OGSA-DAI project homepage. http://www.ogsadai.org.uk/index.php.

Google Scholar

[9]

Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. WEKA-experiences with a java open-source project. Journal of Machine Learning Research, no. 11, pp.2533--2541, 2010.

Digital Library

Google Scholar

Cited By

View all

Zhou XJin QWu BWang WPan JZheng W(2013)Organic streams: Data aggregation and integration based on individual needs2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)10.1109/ICAwST.2013.6765498(535-541)Online publication date: Nov-2013
https://doi.org/10.1109/ICAwST.2013.6765498

Index Terms

Distributed data integration and mining
1. Information systems
  1. Information retrieval
    1. Search engine architectures and scalability
      1. Distributed retrieval
      2. Peer-to-peer retrieval
  2. Information storage systems
    1. Storage architectures
      1. Distributed storage

Recommendations

A distributed architecture for data mining and integration
DADC '09: Proceedings of the second international workshop on Data-aware distributed computing

This paper presents the rationale for a new architecture to support a significant increase in the scale of data integration and data mining. It proposes the composition into one framework of (1) data mining and (2) data access and integration. We name ...
Distributed data mining on grids: services, tools, and applications

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over ...
Mining constrained frequent itemsets from distributed uncertain data

Nowadays, high volumes of massive data can be generated from various sources (e.g.,sensor data from environmental surveillance). Many existing distributed frequent itemset mining algorithms do not allow users to express the itemsets to be mined ...

Comments

Information & Contributors

Information

Published In

iiWAS '11: Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services

December 2011

572 pages

ISBN:9781450307840

DOI:10.1145/2095536

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 December 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Conference

MoMM '11

MoMM '11: The 9th International Conference on Advances in Mobile Computing & Multimedia

December 5 - 7, 2011

Ho Chi Minh City, Vietnam

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
150
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Zhou XJin QWu BWang WPan JZheng W(2013)Organic streams: Data aggregation and integration based on individual needs2013 International Joint Conference on Awareness Science and Technology & Ubi-Media Computing (iCAST 2013 & UMEDIA 2013)10.1109/ICAwST.2013.6765498(535-541)Online publication date: Nov-2013
https://doi.org/10.1109/ICAwST.2013.6765498

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

A distributed architecture for data mining and integration

Distributed data mining on grids: services, tools, and applications

Mining constrained frequent itemsets from distributed uncertain data

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations