2 Search Results for "van Mulligen, Erik"

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DOI: 10.4230/TGDK.1.1.3
Knowledge Engineering Using Large Language Models

Authors: Bradley P. Allen, Lise Stork, and Paul Groth

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages. The emergence of large language models and their capabilities to effectively work with natural language, in its broadest sense, raises questions about the foundations and practice of knowledge engineering. Here, we outline the potential role of LLMs in knowledge engineering, identifying two central directions: 1) creating hybrid neuro-symbolic knowledge systems; and 2) enabling knowledge engineering in natural language. Additionally, we formulate key open research questions to tackle these directions.
Cite as

Bradley P. Allen, Lise Stork, and Paul Groth. Knowledge Engineering Using Large Language Models. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 3:1-3:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{allen_et_al:TGDK.1.1.3,
  author =	{Allen, Bradley P. and Stork, Lise and Groth, Paul},
  title =	{{Knowledge Engineering Using Large Language Models}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:19},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.3},
  URN =		{urn:nbn:de:0030-drops-194777},
  doi =		{10.4230/TGDK.1.1.3},
  annote =	{Keywords: knowledge engineering, large language models}
}
Document
DOI: 10.4230/DagSemProc.05271.16
Towards Mapping-Based Document Retrieval in Heterogeneous Digital Libraries

Authors: Heiner Stuckenschmidt, Wolf Siberski, and Erik van Mulligen

Published in: Dagstuhl Seminar Proceedings, Volume 5271, Semantic Grid: The Convergence of Technologies (2005)

Abstract
In many scientific domains, researchers depend on a timely and efficient access to available publications in their particular area. The increasing availability of publications in electronic form via digital libraries is a reaction to this need. A remaining problem is the fact that the pool of all available publications is distributed between different libraries. In order to increase the availability of information, these different libraries should be linked in such a way, that all the information is available via any one of them. Peer-to-peer technologies provide sophisticated solutions for this kind of loose integration of information sources. In our work, we consider digital libraries that organize documents according to a dedicated classification hierarchy or provide access to information on the basis of a thesaurus. These kinds of access mechanisms have proven to increase the retrieval result and are therefore widely used. On the other hand, this causes new problems as different sources will use different classifications and thesauri to organize information. This means, that we have to be able to mediate between these different structures. Integrating this mediation into the information retrieval process is a problem that to the best of our knowledge has not been addressed before.
Cite as

Heiner Stuckenschmidt, Wolf Siberski, and Erik van Mulligen. Towards Mapping-Based Document Retrieval in Heterogeneous Digital Libraries. In Semantic Grid: The Convergence of Technologies. Dagstuhl Seminar Proceedings, Volume 5271, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{stuckenschmidt_et_al:DagSemProc.05271.16,
  author =	{Stuckenschmidt, Heiner and Siberski, Wolf and van Mulligen, Erik},
  title =	{{Towards Mapping-Based Document Retrieval in Heterogeneous Digital Libraries}},
  booktitle =	{Semantic Grid: The Convergence of Technologies},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{5271},
  editor =	{Carole Goble and Carl Kesselman and York Sure},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05271.16},
  URN =		{urn:nbn:de:0030-drops-3859},
  doi =		{10.4230/DagSemProc.05271.16},
  annote =	{Keywords: Classifications, Concept Matching, Information Retrieval}
}
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