Markus Ackermann

Markus Ackermann
Depiction of Markus Ackermann
Address Work
eccenca GmbH
Hainstraße 8, 04109 Leipzig
Email Office
Phone Work
+49-341-26508028
Fax Work
+49-341-26489305

Short Bio

Markus Ackermann worked as research assistant at the AKSW - KILT group in Leipzig. Before joining AKSW group, he was involved in several Digital Humanities projects by the NLP department and the DH department at Leipzig University as student assistant worker and also supplemented an introductory NLP lecture with hands-on sessions. After switching from teacher's training for Mathematics and English to Computer Science, he received his BSc. at Leipzig University in 2013.

Markus's research interests are in the area of Natural Language Processing, Knowledge Representation & Reasoning and the potential of combining both utilizing Semantic Web paradigms. In the course of his activities he also developed interests in Functional Programming Approaches, Machine Learning, Computational Morphology and possibilities to improve Named Entity recognition therewith.

Past Projects

  • ALIGNEDAligned, Quality-centric Software and Data Engineering
  • Dockerizing Linked DataKnowledge Base Shipping to the Linked Open Data Cloud
  • MMoOnThe Multilingual Morpheme Ontology and Language Inventories
  • NLP2RDFConverting NLP tool output to RDF

Publications

by (Editors: ) [BibTex of ]

News

SANSA 0.7.1 (Semantic Analytics Stack) Released ( 2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann)

2020-01-17T09:52:41+01:00 by Prof. Dr. Jens Lehmann

We are happy to announce SANSA 0.7.1 – the seventh release of the Scalable Semantic Analytics Stack. SANSA employs distributed computing via Apache Spark and Flink in order to allow scalable machine learning, inference and querying capabilities for large knowledge graphs. Read more about "SANSA 0.7.1 (Semantic Analytics Stack) Released"

More Complete Resultset Retrieval from Large Heterogeneous RDF Sources ( 2019-12-05T15:46:09+01:00 Andre Valdestilhas)

2019-12-05T15:46:09+01:00 Andre Valdestilhas

Over recent years, the Web of Data has grown significantly. Various interfaces such as LOD Stats, LOD Laundromat and SPARQL endpoints provide access to hundreds of thousands of RDF datasets, representing billions of facts. Read more about "More Complete Resultset Retrieval from Large Heterogeneous RDF Sources"

DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released ( 2019-09-24T22:41:46+02:00 by Simon Bin)

2019-09-24T22:41:46+02:00 by Simon Bin

Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released"

DBpedia Day @ SEMANTiCS 2019 ( 2019-08-01T10:35:05+02:00 Sandra Bartsch)

2019-08-01T10:35:05+02:00 Sandra Bartsch

 We are happy to announce that SEMANTiCS 2019 will host the 14th DBpedia Community Meeting at the last day of the conference on September 12, 2019. Read more about "DBpedia Day @ SEMANTiCS 2019"

LDK conference @ University of Leipzig ( 2019-03-22T09:21:41+01:00 by Julia Holze)

2019-03-22T09:21:41+01:00 by Julia Holze

With the advent of digital technologies, an ever-increasing amount of language data is now available across various application areas and industry sectors, thus making language data more and more valuable. Read more about "LDK conference @ University of Leipzig"