Simon Bin

@inproceedings{DBLP:conf/www/BuhmannLWB18,

title = {DL-Learner Structured Machine Learning on Semantic Web Data},

author = {Lorenz Bühmann and 

Jens Lehmann and 

Patrick Westphal and 

Simon Bin},

url = {https://doi.org/10.1145/3184558.3186235},

doi = {10.1145/3184558.3186235},

year  = {2018},

date = {2018-01-01},

booktitle = {Companion of the The Web Conference 2018 on The Web Conference 2018, 

WWW 2018, Lyon , France, April 23-27, 2018},

pages = {467--471},

publisher = {ACM},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/ErmilovLSBWSBCP17,

title = {The Tale of Sansa Spark},

author = {Ivan Ermilov and 

Jens Lehmann and 

Gezim Sejdiu and 

Lorenz Bühmann and 

Patrick Westphal and 

Claus Stadler and 

Simon Bin and 

Nilesh Chakraborty and 

Henning Petzka and 

Muhammad Saleem and 

Axel-Cyrille Ngonga Ngomo and 

Hajira Jabeen},

url = {http://ceur-ws.org/Vol-1963/paper552.pdf},

year  = {2017},

date = {2017-01-01},

booktitle = {Proceedings of the ISWC 2017 Posters & Demonstrations and Industry 

Tracks co-located with 16th International Semantic Web Conference 

(ISWC 2017), Vienna, Austria, October 23rd - to - 25th, 2017},

volume = {1963},

publisher = {CEUR-WS.org},

series = {CEUR Workshop Proceedings},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/bigdataconf/BinWLN17,

title = {Implementing scalable structured machine learning for big data in 

the SAKE project},

author = {Simon Bin and 

Patrick Westphal and 

Jens Lehmann and 

Axel Ngonga},

url = {https://doi.org/10.1109/BigData.2017.8258073},

doi = {10.1109/BigData.2017.8258073},

year  = {2017},

date = {2017-01-01},

booktitle = {2017 IEEE International Conference on Big Data (IEEE BigData 2017), 

Boston, MA, USA, December 11-14, 2017},

pages = {1400--1407},

publisher = {IEEE Computer Society},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/semweb/LehmannSBWSEBCS17,

title = {Distributed Semantic Analytics Using the SANSA Stack},

author = {Jens Lehmann and 

Gezim Sejdiu and 

Lorenz Bühmann and 

Patrick Westphal and 

Claus Stadler and 

Ivan Ermilov and 

Simon Bin and 

Nilesh Chakraborty and 

Muhammad Saleem and 

Axel-Cyrille Ngonga Ngomo and 

Hajira Jabeen},

url = {https://doi.org/10.1007/978-3-319-68204-4_15},

doi = {10.1007/978-3-319-68204-4_15},

year  = {2017},

date = {2017-01-01},

booktitle = {The Semantic Web - ISWC 2017 - 16th International Semantic Web Conference, 

Vienna, Austria, October 21-25, 2017, Proceedings, Part II},

volume = {10588},

pages = {147--155},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

abstract = {Over the past decade, vast amounts of machine-readable structured information have become available through the automation of research processes as well as the increasing popularity of knowledge graphs and semantic technologies. A major research challenge today is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and question answering. Most analytics approaches, which scale horizontally (i.e., can be executed in a distributed environment) work on simple feature-vector-based input rather than more expressive knowledge structures. On the other hand, analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases. This software framework paper describes the ongoing project Semantic Analytics Stack (SANSA) which supports expressive and scalable semantic analytics by providing functionality for distributed in-memory computing for RDF data. The library provides APIs for RDF storage, querying using SPARQL and forward chaining inference. It includes several machine learning algorithms for RDF knowledge graphs. The article describes the vision, architecture and use cases of SANSA.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/ecai/BinBLN16,

title = {Towards SPARQL-Based Induction for Large-Scale RDF Data Sets},

author = {Simon Bin and 

Lorenz Bühmann and 

Jens Lehmann and 

Axel-Cyrille Ngonga Ngomo},

url = {https://doi.org/10.3233/978-1-61499-672-9-1551},

doi = {10.3233/978-1-61499-672-9-1551},

year  = {2016},

date = {2016-01-01},

booktitle = {ECAI 2016 - 22nd European Conference on Artificial Intelligence, 

29 August-2 September 2016, The Hague, The Netherlands - Including 

Prestigious Applications of Artificial Intelligence (PAIS 2016)},

volume = {285},

pages = {1551--1552},

publisher = {IOS Press},

series = {Frontiers in Artificial Intelligence and Applications},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{DBLP:conf/tpnc/BinVSM14,

title = {Comparing the Optimization Behaviour of Heuristics with Topology Based 

Visualization},

author = {Simon Bin and 

Sebastian Volke and 

Gerik Scheuermann and 

Martin Middendorf},

url = {https://doi.org/10.1007/978-3-319-13749-0_5},

doi = {10.1007/978-3-319-13749-0_5},

year  = {2014},

date = {2014-01-01},

booktitle = {Theory and Practice of Natural Computing - Third International Conference, 

TPNC 2014, Granada, Spain, December 9-11, 2014. Proceedings},

volume = {8890},

pages = {47--58},

publisher = {Springer},

series = {Lecture Notes in Computer Science},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}