Explore the words cloud of the PROTEUS project. It provides you a very rough idea of what is the project "PROTEUS" about.
The following table provides information about the project.
Coordinator |
BOURNEMOUTH UNIVERSITY
Organization address contact info |
Coordinator Country | United Kingdom [UK] |
Project website | http://www.proteus-bigdata.com |
Total cost | 3˙156˙525 € |
EC max contribution | 3˙156˙525 € (100%) |
Programme |
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)) |
Code Call | H2020-ICT-2015 |
Funding Scheme | RIA |
Starting year | 2015 |
Duration (year-month-day) | from 2015-12-01 to 2018-11-30 |
Take a look of project's partnership.
# | ||||
---|---|---|---|---|
1 | BOURNEMOUTH UNIVERSITY | UK (POOLE) | coordinator | 627˙774.00 |
2 | DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH | DE (KAISERSLAUTERN) | participant | 1˙035˙750.00 |
3 | TREELOGIC TELEMATICA Y LOGICA RACIONAL PARA LA EMPRESA EUROPEA SL | ES (LLANERA ASTURIAS) | participant | 700˙294.00 |
4 | TRILATERAL RESEARCH LTD | UK (LONDON) | participant | 333˙750.00 |
5 | Lambdoop Solutions S.L. | ES (MADRID) | participant | 243˙330.00 |
6 | ARCELORMITTAL INNOVACION INVESTIGACION E INVERSION SL | ES (GOZON) | participant | 215˙625.00 |
7 | TRILATERAL RESEARCH & CONSULTING LLP | UK (LONDON) | participant | 0.00 |
PROTEUS mission is to investigate and develop ready-to-use scalable online machine learning algorithms and interactive visualization techniques for real-time predictive analytics to deal with extremely large data sets and data streams. The developed algorithms and techniques will form a library to be integrated into an enhanced version of Apache Flink, the EU Big Data platform. PROTEUS will contribute to the EU Big Data area by addressing fundamental challenges related to the scalability and responsiveness of analytics capabilities. The requirements are defined by a steelmaking industrial use case. The techniques developed in PROTEUS are however, general, flexible and portable to all data stream-based domains. In particular, the project will go beyond the current state-of-art technology by making the following specific original contributions: i) Real-time scalable machine learning for massive, high-velocity and complex data streams analytics; ii) Real-time hybrid computation, batch data and data streams; iii) Real-time interactive visual analytics for Big Data; iv) Enhancement of Apache Flink, the EU Big Data platform; and v) Real-world industrial validation of the technology developed The PROTEUS impact is manifold: i) strategic, by reducing the gap and dependency from the US technology, empowering the EU Big Data industry through the enrichment of the EU platform Apache Flink; ii) economic, by fostering the development of new skills and new job positions and opportunities towards economic growth; iii) industrial, by considering real-world requirements from industry and by validating the outcome on an operational setting, and iv) scientific, by developing original hybrid and streaming analytic architectures that enable scalable online machine learning strategies and advanced interactive visualisation techniques that are applicable for general data streams in other domains.
Report on scientific dissemination activities – V2 [ | Documents, reports | 2020-02-20 17:17:37 |
PROTEUS factsheet leaflet | Websites, patent fillings, videos etc. | 2020-02-20 17:17:34 |
Catalogue of scientific and technical requirements | Documents, reports | 2020-02-20 17:17:35 |
Updateable-state management prototype implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
Investigative overview of targeted techniques and algorithms | Documents, reports | 2020-02-20 17:17:34 |
Report on community engagement and technology transfer activities – V1 | Documents, reports | 2020-02-20 17:17:34 |
Guidelines for interacting and visualization information in Big Data environments | Documents, reports | 2020-02-20 17:17:34 |
Report on project communication and engagement activities – V1 | Documents, reports | 2020-02-20 17:17:34 |
Declarative language syntax definition | Documents, reports | 2020-02-20 17:17:35 |
Basic scalable streaming algorithms | Demonstrators, pilots, prototypes | 2020-02-20 17:17:35 |
Declarative language prototype implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
Report on scientific dissemination activities – V1 | Documents, reports | 2020-02-20 17:17:34 |
Hybrid computation prototype implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
Hybrid computation tested system | Demonstrators, pilots, prototypes | 2020-02-20 17:17:35 |
Visualization requirements for massive online machine learning strategies | Documents, reports | 2020-02-20 17:17:35 |
First prototype (V1) | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
PROTEUS project website | Websites, patent fillings, videos etc. | 2020-02-20 17:17:35 |
Scenario details and objectives description | Documents, reports | 2020-02-20 17:17:34 |
Scenario development and KPI definition for the PROTEUS solution | Documents, reports | 2020-02-20 17:17:35 |
Scalable Online algorithms in Flink | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
Optimizer finished implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Architecture design for supporting incremental visual methods | Documents, reports | 2020-02-20 17:17:34 |
Report on community engagement and technology transfer activities – V2 | Documents, reports | 2020-02-20 17:17:34 |
Scalable drift and anomaly detection | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Third prototype (V3) | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
PROTEUS evaluation and impact assessment | Documents, reports | 2020-02-20 17:17:34 |
Declarative language finished implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Declarative language tested implementation | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Final demonstrator | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Optimizer Prototype | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Second prototype (V2) | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Software implementation and integration with Apache Flink | Demonstrators, pilots, prototypes | 2020-02-20 17:17:34 |
Scalable online machine learning algorithms for streaming | Demonstrators, pilots, prototypes | 2020-02-20 17:17:33 |
Report on project communication and engagement activities – V2 | Documents, reports | 2020-02-20 17:17:37 |
Take a look to the deliverables list in detail: detailed list of PROTEUS deliverables.
year | authors and title | journal | last update |
---|---|---|---|
2018 |
Daniela Pohl, Abdelhamid Bouchachia, Hermann Hellwagner Batch-based active learning: Application to social media data for crisis management published pages: 232-244, ISSN: 0957-4174, DOI: 10.1016/j.eswa.2017.10.026 |
Expert Systems with Applications 93 | 2020-02-20 |
2015 |
Paris Carbone, Stephan Ewen, Seif Haridi, Asterios Katsifodimos, Volker Markl, Kostas Tzoumas Apache Flink: Stream and Batch Processing in a Single Engine published pages: 28-38, ISSN: , DOI: |
Bulletin of the IEEE Computer Society Technical Committee on Data Engineering December 2015 Vol. 38 No. 4, Is | 2020-02-20 |
2017 |
Bonaventura Del Monte Efficient Migration of Very Large Distributed State for Scalable Streaming Processing published pages: , ISSN: , DOI: |
Proceedings of the VLDB 2017 PhD Workshop 28 August 2017 | 2020-02-20 |
2016 |
Saad Mohamad, Moamar Sayed-Mouchaweh and Abdelhamid Bouchachia Active Learning for Data Streams under Concept Drift and concept evolution published pages: 51-68, ISSN: , DOI: |
ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments STREAMEVOLV-2016, 23 September | 2020-02-20 |
2016 |
DÃaz Morales, R. , & Navia Vázquez, à Improving the efficiency of IRWLS SVMs using parallel Cholesky factorization published pages: 91-98, ISSN: 0167-8655, DOI: 10.1016/j.patrec.2016.08.015 |
Pattern Recognition Letters Volume 84, 1 December 2016 | 2020-02-20 |
2017 |
Roberto DÃaz-Morales, Ãngel Navia-Vázquez LIBIRWLS: A parallel IRWLS library for full and budgeted SVMs published pages: 183-186, ISSN: 0950-7051, DOI: 10.1016/j.knosys.2017.09.007 |
Knowledge-Based Systems 136 | 2020-02-20 |
2016 |
Bouchachia, Abdelhamid; Kalnishkan, Y; Jamil, W. Aggregation Algorithm Vs. Average for Time Series Prediction published pages: 69-82, ISSN: , DOI: |
ECML/PKDD 2016 Workshop on Large-scale Learning from Data Streams in Evolving Environments (STREAMEVOLV-2016) 1 | 2020-02-20 |
2016 |
Mohamad, S., Bouchachia, A. and Sayed-Mouchaweh, M. A Bi-Criteria Active Learning Algorithm for Dynamic Data Streams published pages: 1-13, ISSN: 2162-2388, DOI: 10.1109/TNNLS.2016.2614393 |
IEEE Transactions on Neural Networks and Learning Systems N/A (early access) | 2020-02-20 |
2018 |
Saad Mohamad, Moamar Sayed-Mouchaweh, Abdelhamid Bouchachia Active learning for classifying data streams with unknown number of classes published pages: 1-15, ISSN: 0893-6080, DOI: 10.1016/j.neunet.2017.10.004 |
Neural Networks 98 | 2020-02-20 |
2017 |
José de Jesús Rubio, Abdelhamid Bouchachia MSAFIS: an evolving fuzzy inference system published pages: 2357-2366, ISSN: 1432-7643, DOI: 10.1007/s00500-015-1946-4 |
Soft Computing 21/9 | 2020-02-20 |
2017 |
Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl Blockjoin published pages: 2061-2072, ISSN: 2150-8097, DOI: 10.14778/3151106.3151110 |
Proceedings of the VLDB Endowment 10/13 | 2020-02-20 |
2017 |
M.S. Mouchaweh, A. Bifet, A. Bouchachia, J. Gama, R. Ribeiro ECML/PKDD 2017 Workshop on IoT Large Scale Learning from Data Streams published pages: , ISSN: , DOI: |
2020-02-20 |
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PROTEUS" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.
Thanks. And then put a link of this page into your project's website.
The information about "PROTEUS" are provided by the European Opendata Portal: CORDIS opendata.