Machine Learning and Ontology Engineering

The MOLE group focuses on combining Semantic Web and supervised Machine Learning technologies. The goal is to improve both quality and quantity of available knowledge by extracting, analysing, enriching and linking existing data. To make obtained results readily available for use in other applications, the group also provides several established open source tools, frameworks and demonstrators.

Research Areas

  • Creating knowledge bases from weakly structured data
  • Quality assurance and enhancement in ontologies
  • Semi-automatic instance matching
  • Supervised Machine Learning in OWL/RDF knowledge bases

Projects

  • ALIGNEDAligned, Quality-centric Software and Data Engineering
  • AskNowAskNow is a Question Answering (QA) system for RDF datasets.
  • AskNowAskNow is a Question Answering (QA) system for RDF datasets.
  • ASSESSAutomatic Self Assessment
  • AutoSPARQLConvert a natural language expression to a SPARQL query
  • BDEBig Data Europe
  • BIGBig Data Public Private Forum
  • CubeQAQuestion Answering on Statistical Linked Data
  • DBpediaQuerying Wikipedia like a Semantic Database
  • DBpediaDQUser-driven quality evaluation of DBpedia
  • DBpediaDQCrowdCrowdsourcing DBpedia Quality Assessment
  • DEERRDF Data Extraction and Enrichment Framework
  • DeFactoDeep Fact Validation
  • DEQADeep Web Extraction for Question Answering
  • DL-Learnera tool for supervised Machine Learning in OWL and Description Logics
  • FaceteJavaScript SPARQL-based Faceted Search Library and Browsing Widgets
  • FTSRDF Version of the Financial Transparency System of the European Commission
  • 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
  • GHOPublishing and Interlinking the Global Health Observatory Dataset
  • GOLDGenerating Ontologies from Linked Data
  • HAWKHybrid Question Answering over Linked Data
  • HOBBITHolistic Benchmarking of Big Linked Data
  • JassaJAvascript Suite for Sparql Access
  • jena-sparql-apiA Java library featuring tools for transparently boosting SPARQL query execution.
  • LATCLOD Around-the-Clock
  • LIMESLInk discovery framework for MEtric Spaces
  • LinkedGeoDataadds a spatial dimension to the Web of Data
  • LinkedIdiomsA Multilingual Linked Idioms Data Set
  • LinkedSpendinggovernment spendings from all over the world as Linked Data
  • LOD2Creating Knowledge out of Interlinked Data
  • LODStatsa statement-stream-based approach for gathering comprehensive statistics about RDF datasets
  • MEX VocabularyA Light-Weight Interchange Format for Machine Learning Experiments
  • NIF4OGGDNatural Language Interchange Format for Open German Governmental Data
  • NLP2RDFConverting NLP tool output to RDF
  • OREA tool for the enrichment, repair and validation of OWL based knowledge bases.
  • QAMELQuestion Answering on Mobil Devices
  • RDFUnitan RDF Unit-Testing suite
  • ReDD-ObservatoryUsing the Web of Data for Evaluating the Research-Disease Disparity
  • REXWeb-Scale Extension of RDF Knowledge Bases
  • SAIM(Semi-)Automatic Instance Matcher
  • SAKEWith RDF and Machine Learning Getting Results Faster
  • SANSA-StackOpen source platform for distributed data processing for RDF large-scale datasets
  • SemanticQurana Multilingual Resource for Natural-Language Processing
  • SemMap
  • SML-BenchA Benchmark for Symbolic Supervised Machine Learning from Expressive Structured Data
  • SPARQL2NLconverting SPARQL queries to natural language
  • SparqlAnalyticsI Know What You Did Last Query
  • Sparqlifya SPARQL-SQL rewriter
  • SparqlMapis a SPARQL-to-SQL rewriter
  • TripleCheckMateCrowdsourcing the evaluation of Linked Data
  • USPatentsPublishing and Interlinking the USPTO Patent Data
  • VeriLinksverifying links in an arbitrary linkset

Publications

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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"