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.

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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.

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ESWC 2017 accepted two Demo Papers by AKSW members ( 2017-04-19T10:19:43+02:00 Christopher Schulz)

2017-04-19T10:19:43+02:00 Christopher Schulz

Hello Community! The 14th ESWC, which takes place from May 28th to June 1st 2017 in Portoroz, Slovenia, accepted two demos to be presented at the conference. Read more about them in the following:                                                                         1. Read more about "ESWC 2017 accepted two Demo Papers by AKSW members"

AKSW Colloquium, 10.04.2017, GeoSPARQL on geospatial databases ( 2017-04-07T10:43:55+02:00 by Dr. Matthias Wauer)

2017-04-07T10:43:55+02:00 by Dr. Matthias Wauer

At the AKSW Colloquium, on Monday 10th of April 2017, 3 PM, Matthias Wauer will discuss a paper titled “Ontop of Geospatial Databases“. Read more about "AKSW Colloquium, 10.04.2017, GeoSPARQL on geospatial databases"

AKSW Colloquium, 03.04.2017, RDF Rule Mining ( 2017-03-31T13:39:28+02:00 TommasoSoru)

2017-03-31T13:39:28+02:00 TommasoSoru

At the AKSW Colloquium, on Monday 3rd of April 2017, 3 PM, Tommaso Soru will present the state of his ongoing research titled “Efficient Rule Mining on RDF Data”, where he will introduce Horn Concerto, a novel scalable SPARQL-based approach … Continue reading → Read more about "AKSW Colloquium, 03.04.2017, RDF Rule Mining"

AKSW Colloquium, 27.03.2017, PPO & PPM 2.0: Extending the privacy preference framework to provide finer-grained access control for the Web of Data ( 2017-03-27T10:13:08+02:00 by Marvin Frommhold)

2017-03-27T10:13:08+02:00 by Marvin Frommhold

In the upcoming Colloquium, March the 27th at 3 PM Marvin Frommhold will discuss the paper “PPO & PPM 2.0: Extending the Privacy Preference Framework to provide finer-grained access control for the Web of Data” by Owen Sacco and John G. Read more about "AKSW Colloquium, 27.03.2017, PPO & PPM 2.0: Extending the privacy preference framework to provide finer-grained access control for the Web of Data"

DBpedia @ Google Summer of Code – GSoC 2017 ( 2017-03-13T11:12:50+01:00 Christopher Schulz)

2017-03-13T11:12:50+01:00 Christopher Schulz

DBpedia, one of InfAI’s community projects, will be part of the 5th Google Summer of Code program. The GsoC has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code – GSoC 2017"