SML-Bench: A Benchmark for Symbolic Supervised Machine Learning from Expressive Structured Data

The ultimate goal of SML-Bench is to foster research in machine learning from structured data as well as increase the reproducibility and comparability of algorithms in that area. This is important, since a) the preparation of machine learning tasks in that area involves a significant amount of work and b) there are hardly any cross comparisions across languages as this requires data conversion processes.

Issues Source Code Download Homepage

SML-Bench (Structured Machine Learning Benchmark) is a benchmark for machine learning from structured data. It provides datasets, which contain structured knowledge (beyond plain feature vectors) in languages such as the Web Ontology Language (OWL) or the logic programming language Prolog. For those datasets, SML-Bench defines a number of machine learning tasks, e.g. the prediction of diseases.

Project Team

Publications

by (Editors: ) [BibTex of ]

News

AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction ( 2017-01-20T14:02:35+01:00 by Ivan Ermilov)

2017-01-20T14:02:35+01:00 by Ivan Ermilov

Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction On the upcoming colloquium on 23.01. Read more about "AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction"

PRESS RELEASE: “HOBBIT so far.” is now available ( 2017-01-09T14:22:29+01:00 by Sandra Bartsch)

2017-01-09T14:22:29+01:00 by Sandra Bartsch

The latest release informs about the conferences our team attended in 2016 as well as about the published blogposts. Read more about "PRESS RELEASE: “HOBBIT so far.” is now available"

4th Big Data Europe Plenary at Leipzig University ( 2016-12-16T14:33:41+01:00 by Sandra Bartsch)

2016-12-16T14:33:41+01:00 by Sandra Bartsch

The meeting, hosted by our partner InfAI e. V., took place on the 14th to the 15th of December at the University of Leipzig. Read more about "4th Big Data Europe Plenary at Leipzig University"

SANSA 0.1 (Semantic Analytics Stack) Released ( 2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann)

2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann

Dear all, The Smart Data Analytics group /AKSW are very happy to announce SANSA 0.1 – the initial release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.1 (Semantic Analytics Stack) Released"

AKSW wins award for Best Resources Paper at ISWC 2016 in Japan ( 2016-12-09T15:05:00+01:00 by Sandra Bartsch)

2016-12-09T15:05:00+01:00 by Sandra Bartsch

Our paper, “LODStats: The Data Web Census Dataset”, won the award for Best Resources Paper at the recent conference in Kobe/Japan, which was the premier international forum for Semantic Web and Linked Data Community. Read more about "AKSW wins award for Best Resources Paper at ISWC 2016 in Japan"