M
Max Jakob
Researcher at Free University of Berlin
Publications - 10
Citations - 4806
Max Jakob is an academic researcher from Free University of Berlin. The author has contributed to research in topics: Ontology (information science) & Linked data. The author has an hindex of 6, co-authored 9 publications receiving 3940 citations. Previous affiliations of Max Jakob include Saarland University.
Papers
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Journal ArticleDOI
DBpedia - A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia
Jens Lehmann,Robert Isele,Max Jakob,Anja Jentzsch,Dimitris Kontokostas,Pablo N. Mendes,Sebastian Hellmann,Mohamed Morsey,Patrick van Kleef,Sören Auer,Sören Auer,Christian Bizer +11 more
TL;DR: An overview of the DBpedia community project is given, including its architecture, technical implementation, maintenance, internationalisation, usage statistics and applications, including DBpedia one of the central interlinking hubs in the Linked Open Data (LOD) cloud.
Proceedings ArticleDOI
DBpedia spotlight: shedding light on the web of documents
TL;DR: DBpedia Spotlight, a system for automatically annotating text documents with DBpedia URIs, is developed, and results are evaluated in light of three baselines and six publicly available annotation systems, demonstrating the competitiveness of the system.
Proceedings ArticleDOI
Improving efficiency and accuracy in multilingual entity extraction
TL;DR: This paper discusses some implementation and data processing challenges encountered while developing a new multilingual version of DBpedia Spotlight that is faster, more accurate and easier to configure, and compares the solution to the previous system.
Proceedings Article
DBpedia: A Multilingual Cross-domain Knowledge Base
TL;DR: This paper describes the general DBpedia knowledge base and as well as the DBpedia data sets that specifically aim at supporting computational linguistics tasks that include Entity Linking, Word Sense Disambiguation, Question Answering, Slot Filling and Relationship Extraction.
Proceedings ArticleDOI
Multipedia: enriching DBpedia with multimedia information
TL;DR: This paper addresses the problem of how to enrich ontology instances with candidate images retrieved from existing Web search engines by tapping into the Wikipedia corpus to gather context information for DBpedia instances and takes advantage of image tagging information when this is available to calculate semantic relatedness between instances and candidate images.