Dr. Axel-C. Ngonga Ngomo

Dr. Axel-C. Ngonga Ngomo
Depiction of Dr. Axel-C. Ngonga Ngomo
Address Work
Augustusplatz 10, Room P905, 04109 Leipzig
Email Office
Phone Work
+49-341-97-32362
Fax Work
+49-341-97-32329

Current Projects

  • AGDISTISAgnostic Disambiguation of Named Entities Using Linked Open Data
  • ALOEAssisted Linked Data Consumption Engine
  • ART-e-FACTMedia continuity artefact management
  • ASSESSAutomatic Self Assessment
  • AutoSPARQLConvert a natural language expression to a SPARQL query
  • BDEBig Data Europe
  • BioASQa challenge on large-scale biomedical semantic indexing and question answering
  • BOABOotstrapping linked datA
  • BorderFlowa general-purpose graph clustering tool
  • conTEXTLightweight Text Analytics using Linked Data
  • DEERRDF Data Extraction and Enrichment Framework
  • DeFactoDeep Fact Validation
  • DEQADeep Web Extraction for Question Answering
  • DIESELDistributed Search in Large Enterprise Data
  • FEASIBLEA Featured-Based SPARQL Benchmarks Generation Framework.
  • FOXFederated knOwledge eXtraction Framework
  • GEISERVon Sensordaten zu internetbasierten Geo-Services
  • GeoKnowMaking the Web an Exploratory for Geospatial Knowledge
  • GeoLiftSpatial mapping framework for enriching RDF datasets with Geo-spatial information
  • GERBILGeneral Entity Annotation Benchmark Framework
  • HAWKHybrid Question Answering over Linked Data
  • HOBBITHolistic Benchmarking of Big Linked Data
  • LIMESLInk discovery framework for MEtric Spaces
  • LinkingLODinterlinking knowledge bases
  • LSQLinked SPARQL Queries Dataset
  • QAMELQuestion Answering on Mobil Devices
  • QUETSALA Query Federation Suite for SPARQL
  • Relation Annotation in GENIA
  • REXWeb-Scale Extension of RDF Knowledge Bases
  • SAIM(Semi-)Automatic Instance Matcher
  • SAKEWith RDF and Machine Learning Getting Results Faster
  • SCMSSemantic Content Management Systems
  • SemanticQurana Multilingual Resource for Natural-Language Processing
  • SPARQL2NLconverting SPARQL queries to natural language

Publications

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News

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"