Livrables
This deliverable will present a summary of the activities carried out in Y1, telling a coherent story of the work produced, referring to detailed accounts in the respective deliverables. It will additionally detail the Quality Management and Control policies of the project and explain how they were enforced in the work leading to and in the production of each of the deliverables of Y1. Finally, it will measure success through the evaluation of the measurable outcomes set out in each of the tasks described in this Description of Action, using appropriate key performance indicators.
Flink Real Time Stream Mining Library v1Version 1 of the Flink Real Time Stream Mining Library with evaluation measurements over use case partner data. Basic classification, regression and recommendation methods for combined batch and stream machine learning based on linear models and stochastic gradient descent, also involving low memory synopses for sublinear storage of long-term updatable model components. Baseline measures defined for WP2.
Design and Implementation v1First iteration of the design defined and implementation carried out in T5.1, T5.2, T5.3.
Annual Report, Quality Assurance and Evaluation Period 2This deliverable will present a summary of the activities carried out in Y2, telling a coherent story of the work produced, referring to detailed accounts in the respective deliverables. It will additionally detail the Quality Management and Control policies of the project and explain how they were enforced in the work leading to and in the production of each of the deliverables of Y2. Finally, it will measure success of Y2 activities through the evaluation of the measurable outcomes set out in each of the tasks described in this Description of Action, using appropriate key performance indicators.
Combined Data at Rest and Data in Motion Analysis Platform v2As with all versions of the platform, it will be evaluated using the use case partner data. Delivery plans for M22 (Y2): an advanced demonstration of our platform, i.e. V2, with a larger set of optimization features, operators for unified batch-stream processing, and limited fault tolerance and incremental computation support.
Flink Real Time Stream Mining Library v3Version v3 of the Flink Real Time Stream Mining Library with evaluation measurements over use case partner data. Final version of the online machine learning package tested and evaluated over WP4-5 business cases against Y1 baselines.
Design and Implementation v3Third iteration of the design defined and implementation carried out in T5.1, T5.2, T5.3.
Project Plan Period 1A detailed plan of the activities to be carried during the first year.
Combined Data at Rest and Data in Motion Analysis Platform v3As with all versions of the platform, it will be evaluated using the use case partner data. Delivery plans for M34 (Y3): a full-version platform V3 with all tasks implemented, tested and evaluated over WP4-5 business cases against Y1 baselines and competitor products.
Status report on dissemination activities Period 1Detailed description of dissemination results achieved during Y1 of the project.
Dissemination Roadmap & Project WebsiteDefine the expected project outputs, dissemination and communication activities to be developed during the entire duration of the project. Launch the project website with basic information on the project -- project goals, consortium composition, use cases descriptions -- which will then be updated continuously throughout the duration of the project.
Use case report for actionable knowledge extraction from text informationA report on the extracting actionable knowledge from advanced text data mining using various machine learning algorithms, such as passive-agressive.
Design and Implementation v2Second iteration of the design defined and implementation carried out in T5.1, T5.2, T5.3.
Combined Data at Rest and Data in Motion Analysis Platform v1As with all versions of the platform will be evaluated using the use case partner data. Delivery plans for M10 (Y1): a specification document and a basic demo platform, i.e. V1, with a) subset of query optimization features (like operator chaining) and b) primitive operators necessary for analyzing data at rest and data in motion together.
Status report on dissemination activities Period 2Detailed description of dissemination results achieved during Period 2 of the project.
Project Plan Period 2A detailed plan of the activities to be carried during the second year.
Flink Real Time Stream Mining Library v2Version 2 of the Flink Real Time Stream Mining Library with evaluation measurements over use case partner data. Advanced methods, depending on use cases, potentially including gradient boosted trees, kernel methods, implicit and explicit ALS and tensor factorization, differential privacy and peer-to-peer recommenders.
A high level declarative language for MLA programming model to express different use-cases in our high-level language, and an easy to use declarative language for using ML algorithms on massive dataset.
First iteration of the field trials and evaluation carried out in T5.4.
Flink deployment softwareA deployment tool for automatic installation of Flink on a cluster. It consists of the Chef cookbooks on Karamel for the Flink stack.
Flink interactive environmentAn interactive data analytics tool for Apache Flink that consists of (i) a REPL or language shell with an interactive environment that takes a user inputs, evaluates them, and returns the result to the user quickly, and (ii) a web-based environment, based on Zeppelin, that enables interactive data analyses.
Flink on Hops/HadoopExtension and revision of D3.1 addressing integration of Apache Flink into Hops/Hadoop ecosystem
Field Trials and Evaluation v2Second iteration of the field trials and evaluation carried out in T5.4.
Field Trials and Implementation v3Third iteration of the field trials and evaluation carried out in T5.4.
Publications
Auteurs:
Philipp M. Grulich, René Saitenmacher, Jonas Traub, Sebastian Breß, Tilmann Rabl, Volker Markl
Publié dans:
21st International Conference on Extending Database Technology (EDBT), 2018, 2018, ISBN 978-3-89318-078-3
Éditeur:
Open Proceedings
DOI:
10.5441/002/edbt.2018.51
Auteurs:
Jonas Traub, Sebastian Breß, Tilmann Rabl, Asterios Katsifodimos, Volker Markl
Publié dans:
Proceedings of the 2017 Symposium on Cloud Computing - SoCC '17, 2017, Page(s) 586-597, ISBN 9781-450350280
Éditeur:
ACM Press
DOI:
10.1145/3127479.3131621
Auteurs:
Philipp M. Grulich, Tilmann Rabl, Volker Markl, Csaba Sidló, Andras Benczur
Publié dans:
20th International Conference on Extending Database Technology (EDBT), 2017, 2017
Éditeur:
CEUR Workshop Proceedings
Auteurs:
Jonas Traub, Nikolaas Steenbergen, Philipp M. Grulich, Tilmann Rabl, Volker Markl
Publié dans:
20th International Conference on Extending Database Technology (EDBT), 2017, 2017, ISBN 978-3-89318-073-8
Éditeur:
Open Proceedings
DOI:
10.5441/002/edbt.2017.61
Auteurs:
Andreas Kunft, Alexander Alexandrov, Asterios Katsifodimos, Volker Markl
Publié dans:
Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond - BeyondMR '16, 2016, Page(s) 1-4, ISBN 9781-450343114
Éditeur:
ACM Press
DOI:
10.1145/2926534.2926540
Auteurs:
Alexander Alexandrov, Andreas Salzmann, Georgi Krastev, Asterios Katsifodimos, Volker Markl
Publié dans:
Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16, 2016, Page(s) 2073-2076, ISBN 9781-450335317
Éditeur:
ACM Press
DOI:
10.1145/2882903.2899396
Auteurs:
Jeyhun Karimov, Tilmann Rabl, Asterios Katsifodimos, Roman Samarev, Henri Heiskanen, Volker Markl
Publié dans:
2018 IEEE 34th International Conference on Data Engineering (ICDE), 2018, Page(s) 1507-1518, ISBN 978-1-5386-5520-7
Éditeur:
IEEE
DOI:
10.1109/ICDE.2018.00169
Auteurs:
Jonas Traub Philipp Grulich, Alejandro Rodríguez Cuéllar Sebastian Breß Asterios Katsifodimos Tilmann Rabl Volker Markl
Publié dans:
22nd International Conference on Extending Database Technology (EDBT), 2019, 2019
Éditeur:
Open Proceedings
Auteurs:
Behrouz Derakhshan, Alireza Rezaei Mahdiraji, Tilmann Rabl, and Volker Markl
Publié dans:
22nd International Conference on Extending Database Technology (EDBT), 2019, 2019
Éditeur:
Open Proceedings
Auteurs:
Róbert Pálovics, Domokos Kelen, András A. Benczúr
Publié dans:
Proceedings of the Eleventh ACM Conference on Recommender Systems - RecSys '17, 2017, Page(s) 400-401, ISBN 9781-450346528
Éditeur:
ACM Press
DOI:
10.1145/3109859.3109937
Auteurs:
Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr
Publié dans:
RecSys 2017 poster, 2017
Éditeur:
ACM
Auteurs:
Erzsébet Frigó, Róbert Pálovics, Domokos Kelen, Levente Kocsis, András A. Benczúr
Publié dans:
RecTemp 2017 – workshop on reasoning on temporal aspects in user modeling in conjunction with RecSys 2017, 2017
Éditeur:
ACM
Auteurs:
Zoltan Zvara, Peter G.N. Szabo, Gabor Hermann, Andras Benczur
Publié dans:
2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2017, Page(s) 235-242, ISBN 978-1-5090-6558-5
Éditeur:
IEEE
DOI:
10.1109/fas-w.2017.153
Auteurs:
Domokos M. Kelen, Dániel Berecz, Ferenc Béres, András A. Benczúr
Publié dans:
Proceedings of the ACM Recommender Systems Challenge 2018 on - RecSys Challenge '18, 2018, Page(s) 1-4, ISBN 9781-450365864
Éditeur:
ACM Press
DOI:
10.1145/3267471.3267477
Auteurs:
Paris Carbone, Jonas Traub, Asterios Katsifodimos, Seif Haridi, Volker Markl
Publié dans:
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16, 2016, Page(s) 1201-1210, ISBN 9781-450340731
Éditeur:
ACM Press
DOI:
10.1145/2983323.2983807
Auteurs:
Christoph Boden, Andrea Spina, Tilmann Rabl, Volker Markl
Publié dans:
Proceedings of the 4th Algorithms and Systems on MapReduce and Beyond - BeyondMR'17, 2017, Page(s) 1-10, ISBN 9781-450350198
Éditeur:
ACM Press
DOI:
10.1145/3070607.3070612
Auteurs:
Tilmann Rabl, Hans-Arno Jacobsen
Publié dans:
Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17, 2017, Page(s) 315-330, ISBN 9781-450341974
Éditeur:
ACM Press
DOI:
10.1145/3035918.3064052
Auteurs:
Paul Cao, Bhaskar Gowda, Seetha Lakshmi, Chinmayi Narasimhadevara, Patrick Nguyen, John Poelman, Meikel Poess, Tilmann Rabl
Publié dans:
Performance Evaluation and Benchmarking. Traditional - Big Data - Interest of Things, Numéro 10080, 2017, Page(s) 24-44, ISBN 978-3-319-54333-8
Éditeur:
Springer International Publishing
DOI:
10.1007/978-3-319-54334-5_3
Auteurs:
Quoc-Cuong To, Juan Soto, Volker Markl
Publié dans:
The VLDB Journal, Numéro 27/6, 2018, Page(s) 847-872, ISSN 1066-8888
Éditeur:
Springer Verlag
DOI:
10.1007/s00778-018-0514-9
Auteurs:
Andreas Kunft, Asterios Katsifodimos, Sebastian Schelter, Tilmann Rabl, Volker Markl
Publié dans:
Proceedings of the VLDB Endowment - Proceedings of the 43rd International Conference on Very Large Data Bases, Numéro 10/13, 2017, Page(s) 2061-2072, ISSN 2150-8097
Éditeur:
VLDB Endowment
Auteurs:
Ferenc Béres, Róbert Pálovics, Anna Oláh, András A. Benczúr
Publié dans:
Applied Network Science, Numéro 3/1, 2018, ISSN 2364-8228
Éditeur:
Springer Open
DOI:
10.1007/s41109-018-0080-5
Auteurs:
András A. Benczúr, Róbert Pálovics, Márton Balassi, Volker Markl, Tilmann Rabl, Juan Soto, Björn Hovstadius, Jim Dowling,Seif Haridi
Publié dans:
ERCIM News, Numéro 107, 2016, Page(s) 31-32
Éditeur:
ERCIM EEIG
Auteurs:
András A. Benczúr, Levente Kocsis, Róbert Pálovics
Publié dans:
2018
Éditeur:
MTA SZTAKI
Recherche de données OpenAIRE...
Une erreur s’est produite lors de la recherche de données OpenAIRE
Aucun résultat disponible