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Neue Publikationen
Privacy-Preserving Stress Detection Using Smartwatch Health Data
Privacy-Preserving Sentiment Analysis on Twitter
Using Differential Equation Inspired Machine Learning for Valve Faults Prediction
Privacy at Risk: Exploiting Similarities in Health Data for Identity Inference
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M. Junghanns's Publikationen (18)
Rost, C
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Gomez, K
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Taeschner, M
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Fritzsche, P
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Schons, L
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Christ, L
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Adameit, T
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Junghanns, M
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Rahm, E
Distributed temporal graph analytics with GRADOOP
VLDB Journal 2021 Special Issue Paper
2021-05
Junghanns, Martin
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Kießling, Max
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Teichmann, Niklas
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Gomez, Kevin
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Petermann, Andre
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Rahm, Erhard
Declarative and distributed graph analytics with GRADOOP
PVLDB
2018-08
Green, Alastair
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Junghanns, Martin
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Kießling, Max
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Lindaaker, Tobias
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Plantikow, Stefan
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Selmer, Petra
openCypher: New Directions in Property Graph Querying
Proc. EDBT (tutorial paper)
2018-03
Petermann, A.
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Junghanns, M.
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Rahm, E.
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DIMSpan - Transactional Frequent Subgraph Mining with Distributed In-Memory Dataflow Systems
Proc. Int. Conf. on Big Data Computing, Applications and Technologies (BDCAT) 2017, pp 237-246
2017-12
Junghanns, M.
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Kießling, M.
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Averbuch, A.,
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Petermann, A.
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Rahm, E.
Cypher-based Graph Pattern Matching in Gradoop
Proc. ACM SIGMOD workshop on Graph Data Management Experiences and Systems (GRADES)
2017-05
Junghanns, M.
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Petermann, A.
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Rahm, E.
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Distributed Grouping of Property Graphs with GRADOOP
Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017
2017-03
Junghanns, M.
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Petermann, A.
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Teichmann, N.
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Rahm, E.
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The Big Picture: Understanding large-scale graphs using Graph Grouping with GRADOOP
Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017 (Demo paper)
2017-03
Kemper, S.
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Petermann, A.
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Junghanns, M.
Distributed FoodBroker: Skalierbare Generierung graphbasierter Geschäftsprozessdaten.
Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017 (Workshops)
2017-03
Junghanns, Martin
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Petermann, Andre
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Neumann, Martin
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Rahm, Erhard
Management and Analysis of Big Graph Data: Current Systems and Open Challenges
In: Handbook of Big Data Technologies (eds.: A. Zomaya, S. Sakr) , Springer 2017, to appear
2017-02
Petermann, A.
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Junghanns, M.
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Kemper, S.
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Gomez, K.
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Teichmann, N.
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Rahm, E.
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Graph Mining for Complex Data Analytics
Proc. ICDM 2016 (Demo paper)
2016-12
Junghanns, M.
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Petermann, A.
Verteilte Graphanalyse mit Gradoop
JavaSPEKTRUM 05/2016
2016-10
Petermann, A.
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Junghanns, M.
Scalable Business Intelligence with Graph Collections
it - Information Technology, Special Issue: Big Data Analytics, Vol. 58 (4), 2016, pp. 166–175
2016-08
Junghanns, M.
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Petermann, A.
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Teichmann, N.
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Gomez, K.
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Rahm, E.
Analyzing Extended Property Graphs with Apache Flink
Proc. Int. SIGMOD workshop on Network Data Analytics (NDA)
2016-07
Junghanns, M.
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Petermann, A.
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Gomez, K.
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Rahm, E.
GRADOOP: Scalable Graph Data Management and Analytics with Hadoop
Techn. Report, Univ. of Leipzig, arXiv:1506.00548, June 2015
2015-06
Petermann, A.
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Junghanns, M.
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Müller, R.
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Rahm, E.
Graph-based Data Integration and Business Intelligence with BIIIG
Proc. VLDB Conf., 2014 (Demo paper)
2014-09
Petermann, A.
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Junghanns, M.
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Müller, R.
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Rahm, E.
FoodBroker - Generating Synthetic Datasets for Graph-Based Business Analytics
5th Workshop on Big Data Benchmarking (WBDB 2014), LNCS 8991, 2015
2014-08
Petermann, A.
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Junghanns, M.
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Müller, R.
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Rahm, E.
BIIIG : Enabling Business Intelligence with Integrated Instance Graphs
5th International Workshop on Graph Data Management (GDM 2014)
2014-03