Explore the words cloud of the GraphInt project. It provides you a very rough idea of what is the project "GraphInt" about.
The following table provides information about the project.
Coordinator |
UNIVERSITE DE FRIBOURG
Organization address contact info |
Coordinator Country | Switzerland [CH] |
Project website | https://exascale.info/GraphInt |
Total cost | 1˙998˙339 € |
EC max contribution | 1˙998˙339 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2015-CoG |
Funding Scheme | ERC-COG |
Starting year | 2016 |
Duration (year-month-day) | from 2016-08-01 to 2021-07-31 |
Take a look of project's partnership.
# | ||||
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1 | UNIVERSITE DE FRIBOURG | CH (FRIBOURG) | coordinator | 1˙998˙339.00 |
The present proposal tackles fundamental problems in data management, leveraging expressive, large-scale and heterogeneous graph structures in order to integrate both unstructured (e.g., text) and structured (e.g., relational) content. Integrating heterogeneous content has become a key hurdle in the deployment of Big Data applications, due to the meteoric rise of both machine and user-generated data storing information in a variety of formats. Traditional integration techniques cleaning up, fusing and then mapping heterogeneous data onto rigid abstractions fall short of accurately capturing the complexity and wild heterogeneity of today’s information. Having closely followed the emergence of heterogeneous information sources online, I am convinced that only an interdisciplinary approach drawing both from classical data management and from large-scale Web information processing techniques can solve the formidable data integration challenges that they pose. The following project proposes an ambitious overhaul of information integration techniques embracing the scale and heterogeneity of today’s data. I propose the use of expressive and heterogeneous graphs of entities to continuously and dynamically interrelate disparate pieces of content while capturing their idiosyncrasies. The following project focuses on three core issues related to large-scale and heterogeneous information graphs: i) the effective extraction of fined-grained information from unstructured sources and their proper integration into large-scale heterogeneous and probabilistic graphs, ii) the creation of novel physical storage structures and primitives to durably and efficiently manage the profusion of data considered by such graphs using clusters of commodity machines, and iii) the development of logical data abstraction mechanisms facilitating the effective and efficient resolution of complex analytic and data integration queries on top of the physical layer.
year | authors and title | journal | last update |
---|---|---|---|
2019 |
Michael Luggen, Djellel Difallah, Cristina Sarasua, Gianluca Demartini, and Philippe Cudre-Mauroux Non-Parametric Class Completeness Estimators for Collaborative Knowledge Graphs — The Case of Wikidata published pages: , ISSN: , DOI: |
International Semantic Web Conference (ISWC) 2019 | 2019-10-01 |
2019 |
Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux Accuracy Evaluation of Overlapping and Multi-resolution Clustering Algorithms on Large Datasets published pages: , ISSN: , DOI: |
BigComp 2019 | 2019-04-13 |
2019 |
Alisa Smirnova, Philippe Cudré-Mauroux Relation Extraction Using Distant Supervision published pages: 1-35, ISSN: 0360-0300, DOI: 10.1145/3241741 |
ACM Computing Surveys 51/5 | 2019-04-13 |
2019 |
Alberto Lerner, Rana Hussein, Philippe Cudré-Mauroux The Case for Network Accelerated Query Processing published pages: , ISSN: , DOI: |
CIDR 2019 | 2019-04-13 |
2019 |
Natalia Ostapuk, Jie Yang, Philippe Cudré-Mauroux ActiveLink: Deep Active Learning for Link Prediction in Knowledge Graphs. published pages: , ISSN: , DOI: |
The Web Conf (WWW 2019) | 2019-04-13 |
2019 |
Dingqi Yang, Bingqing Qu, Philippe Cudre-Mauroux Privacy-Preserving Social Media Data Publishing for Personalized Ranking-Based Recommendation published pages: 507-520, ISSN: 1041-4347, DOI: 10.1109/tkde.2018.2840974 |
IEEE Transactions on Knowledge and Data Engineering 31/3 | 2019-04-13 |
2018 |
Leye Wang, Gehua Qin, Dingqi Yang, Xiao Han, Xiaojuan Ma Geographic Differential Privacy for Mobile Crowd Coverage Maximization published pages: 200-207, ISSN: , DOI: |
AAAI18 | 2019-04-13 |
2019 |
Dingqi Yang, Bin Li, Laura Rettig, Philippe Cudre-Mauroux D2 HistoSketch: Discriminative and Dynamic Similarity-Preserving Sketching of Streaming Histograms published pages: 1-1, ISSN: 1041-4347, DOI: 10.1109/tkde.2018.2867468 |
IEEE Transactions on Knowledge and Data Engineering | 2019-04-13 |
2019 |
Jie Yang, Alisa Smirnova, Dingqi Yang, Gianluca Demartini, Yuan Lu, Philippe Cudre-Mauroux Scalpel-CD: Leveraging Crowdsourcing and Deep Probabilistic Modeling for Debugging Noisy Training Data published pages: , ISSN: , DOI: |
The Web Conf (WWW 2019) | 2019-04-13 |
2019 |
Dingqi Yang, Bingqing Qu, Jie Yang, Philippe Cudre-Mauroux Revisiting User Mobility and Social Relationships in LBSNs: A Hypergraph Embedding Approach published pages: , ISSN: , DOI: |
The Web Conf (WWW 2019) | 2019-04-13 |
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "GRAPHINT" project.
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The information about "GRAPHINT" are provided by the European Opendata Portal: CORDIS opendata.
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