MEX Vocabulary: A Light-Weight Interchange Format for Machine Learning Experiments

MEX Vocabulary: A Light-Weight Interchange Format for Machine Learning Experiments

Issues Source Code Download

Over the last decades many machine learning experiments have been published, giving benefit to the scientific progress. In order to compare machine-learning experiment results with each other and collaborate positively, they need to be performed thoroughly on the same computing environment, using the same sample datasets and algorithm configurations. Besides this, practical experience shows that scientists and engineers tend to have large output data in their experiments, which is both difficult to analyze and archive properly without provenance metadata. However, the Linked Data community still misses a light-weight specification for interchanging machine-learning metadata over different architectures to achieve a higher level of interoperability. MEX provides a prompt method to describe experiments with a special focus on data provenance and fulfills the requirements for a long-term maintenance

Publications

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News

SANSA 0.2 (Semantic Analytics Stack) Released ( 2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann)

2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann

The AKSW and Smart Data Analytics groups are happy to announce SANSA 0.2 – the second release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.2 (Semantic Analytics Stack) Released"

AKSW at ESWC 2017 ( 2017-06-12T10:53:35+02:00 Christopher Schulz)

2017-06-12T10:53:35+02:00 Christopher Schulz

Hello Community! The ESWC 2017 just ended and we give a short report of the course at the conference, especially regarding the AKSW-Group. Our members Dr. Muhammad Saleem, Dr. Mohamed Ahmed Sherif, Claus Stadler, Michael Röder, Prof. Dr. Read more about "AKSW at ESWC 2017"

Four papers accepted at WI 2017 ( 2017-06-10T15:01:31+02:00 Christopher Schulz)

2017-06-10T15:01:31+02:00 Christopher Schulz

Hello Community! We proudly announce that The International Conference on Web Intelligence (WI) accepted four papers by our group. The WI takes place in Leipzig between the 23th – 26th of August. Read more about "Four papers accepted at WI 2017"

AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data. ( 2017-05-26T13:51:11+02:00 by Diego Moussallem)

2017-05-26T13:51:11+02:00 by Diego Moussallem

At the AKSW Colloquium, on Monday 29th of May 2017, 3 PM, Diego Moussallem will present two papers related to his topic. First paper titled “Using BabelNet to Improve OOV Coverage in SMT” of Du et al. Read more about "AKSW Colloquium, 29.05.2017, Addressing open Machine Translation problems with Linked Data."

SML-Bench 0.2 Released ( 2017-05-11T13:01:45+02:00 by Patrick Westphal)

2017-05-11T13:01:45+02:00 by Patrick Westphal

Dear all, we are happy to announce the 0.2 release of SML-Bench, our Structured Machine Learning benchmark framework. SML-Bench provides full benchmarking scenarios for inductive supervised machine learning covering different knowledge representation languages like OWL and Prolog. Read more about "SML-Bench 0.2 Released"