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.
  • projects:SemMap
  • 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
  • SemanticQurana Multilingual Resource for Natural-Language Processing
  • 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
  • VeriLinksverifying links in an arbitrary linkset

Publications

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News

AKSW Colloquium, 18.07.2016, AEGLE and node2vec ( 2016-07-18T14:56:44+02:00 TommasoSoru)

2016-07-18T14:56:44+02:00 TommasoSoru

On Monday 18.07.2016, Kleanthi Georgala will give her Colloquium presentation for her paper “An Efficient Approach for the Generation of Allen Relations”, that was accepted at the European Conference on Artificial Intelligence (ECAI) 2016. Read more about "AKSW Colloquium, 18.07.2016, AEGLE and node2vec"

AKSW Colloquium, 04.07.2016. Big Data, Code Quality. ( 2016-06-29T12:34:35+02:00 by Ivan Ermilov)

2016-06-29T12:34:35+02:00 by Ivan Ermilov

On the upcoming Monday (04.07.2016), AKSW group will discuss topics related to Semantic Web and Big Data as well as programming languages and code quality. Read more about "AKSW Colloquium, 04.07.2016. Big Data, Code Quality."

Accepted Papers of AKSW Members @ Semantics 2016 ( 2016-06-27T12:50:01+02:00 by Sandra Bartsch)

2016-06-27T12:50:01+02:00 by Sandra Bartsch

This year’s SEMANTiCS conference which is taking place between September 12 – 15, 2016 in Leipzig recently invited for the submission of research papers on semantic technologies. Read more about "Accepted Papers of AKSW Members @ Semantics 2016"

AKSW Colloquium, 27.06.2016, When owl:sameAs isn’t the Same + Towards Versioning for Arbitrary RDF Data ( 2016-06-26T15:46:24+02:00 by Marvin Frommhold)

2016-06-26T15:46:24+02:00 by Marvin Frommhold

In the next Colloquium, June the 27th at 3 PM, two papers will be presented: When owl:sameAs isn’t the Same: An Analysis of Identity in Linked Data André Valdestilhas will present the paper “When owl:sameAs isn’t the Same: An Analysis of Identity … Continue reading → Read more about "AKSW Colloquium, 27.06.2016, When owl:sameAs isn’t the Same + Towards Versioning for Arbitrary RDF Data"

Should I publish my dataset under an open license? ( 2016-06-22T11:41:28+02:00 by Dr.-Ing. Sebastian Hellmann)

2016-06-22T11:41:28+02:00 by Dr.-Ing. Sebastian Hellmann

Undecided, stand back we know flowcharts:   Taken from my slides for my keynote  at TKE: Linguistic Linked Open Data, Challenges, Approaches, Future Work from Sebastian Hellmann Read more about "Should I publish my dataset under an open license?"