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

  • AgriNepalDataOntology Based Data Access and Integration for Improving the Effectiveness of Farming in Nepal
  • 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
  • DIESELDistributed Search in Large Enterprise Data
  • 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.
  • KupferDigitalDatenökosystem für die digitale Materialentwicklung auf Basis Ontologie-basierter digitaler Repräsentationen von Kupfer und Kupferlegierungen
  • 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
  • LinkingLODinterlinking knowledge bases
  • LOD2Creating Knowledge out of Interlinked Data
  • LODStatsa statement-stream-based approach for gathering comprehensive statistics about RDF datasets
  • mCLIENTEffiziente Schnittstellen für Datenbereitsteller
  • MEX VocabularyA Light-Weight Interchange Format for Machine Learning Experiments
  • Neural SPARQL MachinesTranslating natural language into machine language for data access.
  • 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
  • QROWDThe power of the Qrowd combines with RDF
  • RDFUnitan RDF Unit-Testing suite
  • ReDD-ObservatoryUsing the Web of Data for Evaluating the Research-Disease Disparity
  • REXWeb-Scale Extension of RDF Knowledge Bases
  • SAGESemantic Geospatial Analytics
  • 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
  • SLIPOScalable Linking and Integration of Big POI data
  • 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
  • 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

DBpedia Tutorial @ Knowledge Graph Conference 2021 ( 2021-04-09T13:20:50+02:00 by Julia Holze)

2021-04-09T13:20:50+02:00 by Julia Holze

On May 4, 2021 we will organize a tutorial at the Knowledge Graph Conference (KGC) 2021. Read more about "DBpedia Tutorial @ Knowledge Graph Conference 2021"

DBpedia @ Google Summer of Code program 2021 ( 2021-03-15T09:41:22+01:00 by Julia Holze)

2021-03-15T09:41:22+01:00 by Julia Holze

DBpedia, one of InfAI’s community projects, will participate in the Google Summer of Code (GSoC) program for the 10th time. The GsoC program has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code program 2021"

DBpedia’s New Website ( 2021-01-28T12:42:40+01:00 by Julia Holze)

2021-01-28T12:42:40+01:00 by Julia Holze

We are proud to announce the completion of the new DBpedia website. Read more about "DBpedia’s New Website"

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"