LODStats: a statement-stream-based approach for gathering comprehensive statistics about RDF datasets

LODStats is a statement-stream-based approach for gathering comprehensive statistics about datasets adhering to the Resource Description Framework (RDF). LODStats is based on the declarative description of statistical dataset characteristics. Its main advantages over other approaches are a smaller memory footprint and significantly better performance and scalability. We integrated LODStats into the CKAN dataset metadata registry and obtained a comprehensive picture of the current state of the Data Web.

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AKSW Colloquium, 28.11.2016, NED using PBOH + Large-Scale Learning of Relation-Extraction Rules. ( 2016-11-26T12:30:29+01:00 by Diego Moussallem)

2016-11-26T12:30:29+01:00 by Diego Moussallem

In the upcoming Colloquium, November the 28th at 3 PM, two papers will be presented: Probabilistic Bag-Of-Hyperlinks Model for Entity Linking Diego Moussallem will discuss the paper “Probabilistic Bag-Of-Hyperlinks Model for Entity Linking” by Octavian-Eugen Ganea et. al. Read more about "AKSW Colloquium, 28.11.2016, NED using PBOH + Large-Scale Learning of Relation-Extraction Rules."

Accepted paper in AAAI 2017 ( 2016-11-14T14:48:46+01:00 by Mohamed Sherif)

2016-11-14T14:48:46+01:00 by Mohamed Sherif

Hello Community! Read more about "Accepted paper in AAAI 2017"

AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet ( 2016-10-17T09:55:50+02:00 by Marvin Frommhold)

2016-10-17T09:55:50+02:00 by Marvin Frommhold

In the upcoming Colloquium, October the 17th at 3 PM, two papers will be presented: Version Control for RDF Triple Stores Marvin Frommhold will discuss the paper “Version Control for RDF Triple Stores” by Steve Cassidy and James Ballantine which forms the foundation … Continue reading → Read more about "AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet"

LIMES 1.0.0 Released ( 2016-10-14T11:38:31+02:00 by Kleanthi Georgala)

2016-10-14T11:38:31+02:00 by Kleanthi Georgala

Dear all, the LIMES Dev team is happy to announce LIMES 1.0.0. LIMES, the Link Discovery Framework for Metric Spaces, is a link discovery framework for the Web of Data. Read more about "LIMES 1.0.0 Released"

DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released ( 2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann)

2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann

Dear all, the Smart Data Analytics group at AKSW is happy to announce DL-Learner 1.3. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released"