3 Search Results for "Janssen, Jeroen"

Document
Survey
DOI: 10.4230/TGDK.3.1.3
Uncertainty Management in the Construction of Knowledge Graphs: A Survey

Authors: Lucas Jarnac, Yoan Chabot, and Miguel Couceiro

Published in: TGDK, Volume 3, Issue 1 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 1

Abstract
Knowledge Graphs (KGs) are a major asset for companies thanks to their great flexibility in data representation and their numerous applications, e.g., vocabulary sharing, Q&A or recommendation systems. To build a KG, it is a common practice to rely on automatic methods for extracting knowledge from various heterogeneous sources. However, in a noisy and uncertain world, knowledge may not be reliable and conflicts between data sources may occur. Integrating unreliable data would directly impact the use of the KG, therefore such conflicts must be resolved. This could be done manually by selecting the best data to integrate. This first approach is highly accurate, but costly and time-consuming. That is why recent efforts focus on automatic approaches, which represent a challenging task since it requires handling the uncertainty of extracted knowledge throughout its integration into the KG. We survey state-of-the-art approaches in this direction and present constructions of both open and enterprise KGs. We then describe different knowledge extraction methods and discuss downstream tasks after knowledge acquisition, including KG completion using embedding models, knowledge alignment, and knowledge fusion in order to address the problem of knowledge uncertainty in KG construction. We conclude with a discussion on the remaining challenges and perspectives when constructing a KG taking into account uncertainty.
Cite as

Lucas Jarnac, Yoan Chabot, and Miguel Couceiro. Uncertainty Management in the Construction of Knowledge Graphs: A Survey. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 1, pp. 3:1-3:48, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{jarnac_et_al:TGDK.3.1.3,
  author =	{Jarnac, Lucas and Chabot, Yoan and Couceiro, Miguel},
  title =	{{Uncertainty Management in the Construction of Knowledge Graphs: A Survey}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:48},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.1.3},
  URN =		{urn:nbn:de:0030-drops-233733},
  doi =		{10.4230/TGDK.3.1.3},
  annote =	{Keywords: Knowledge reconciliation, Uncertainty, Heterogeneous sources, Knowledge graph construction}
}
Document
DOI: 10.4230/LIPIcs.ICLP.2010.34
Communicating Answer Set Programs

Authors: Kim Bauters, Jeroen Janssen, Steven Schockaert, Dirk Vermeir, and Martine De Cock

Published in: LIPIcs, Volume 7, Technical Communications of the 26th International Conference on Logic Programming (2010)

Abstract
Answer set programming is a form of declarative programming that has proven very successful in succinctly formulating and solving complex problems. Although mechanisms for representing and reasoning with the combined answer set programs of multiple agents have already been proposed, the actual gain in expressivity when adding communication has not been thoroughly studied. We show that allowing simple programs to talk to each other results in the same expressivity as adding negation-as-failure. Furthermore, we show that the ability to focus on one program in a network of simple programs results in the same expressivity as adding disjunction in the head of the rules.
Cite as

Kim Bauters, Jeroen Janssen, Steven Schockaert, Dirk Vermeir, and Martine De Cock. Communicating Answer Set Programs. In Technical Communications of the 26th International Conference on Logic Programming. Leibniz International Proceedings in Informatics (LIPIcs), Volume 7, pp. 34-43, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{bauters_et_al:LIPIcs.ICLP.2010.34,
  author =	{Bauters, Kim and Janssen, Jeroen and Schockaert, Steven and Vermeir, Dirk and De Cock, Martine},
  title =	{{Communicating Answer Set Programs}},
  booktitle =	{Technical Communications of the 26th International Conference on Logic Programming},
  pages =	{34--43},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-17-0},
  ISSN =	{1868-8969},
  year =	{2010},
  volume =	{7},
  editor =	{Hermenegildo, Manuel and Schaub, Torsten},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2010.34},
  URN =		{urn:nbn:de:0030-drops-25813},
  doi =		{10.4230/LIPIcs.ICLP.2010.34},
  annote =	{Keywords: }
}
Document
DOI: 10.4230/LIPIcs.ICLP.2010.64
Efficient Solving of Time-dependent Answer Set Programs

Authors: Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, and Martine De Cock

Published in: LIPIcs, Volume 7, Technical Communications of the 26th International Conference on Logic Programming (2010)

Abstract
Answer set programs with time predicates are useful to model systems whose properties depend on time, like for example gene regulatory networks. A state of such a system at time point t then corresponds to the literals of an answer set that are grounded with time constant t. An important task when modelling time-dependent systems is to find steady states from which the system's behaviour does not change anymore. This task is complicated by the fact that it is typically not known in advance at what time steps these steady states occur. A brute force approach of estimating a time upper bound tmax and grounding and solving the program w.r.t. that upper bound leads to a suboptimal solving time when the estimate is too low or too high. In this paper we propose a more efficient algorithm for solving Markovian programs, which are time-dependent programs for which the next state depends only on the previous state. Instead of solving these Markovian programs for a long time interval {0,...,tmax}, we successively find answer sets of parts of the grounded program. Our approach guarantees the discovery of all steady states and cycles while avoiding unnecessary extra work.
Cite as

Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, and Martine De Cock. Efficient Solving of Time-dependent Answer Set Programs. In Technical Communications of the 26th International Conference on Logic Programming. Leibniz International Proceedings in Informatics (LIPIcs), Volume 7, pp. 64-73, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{fayruzov_et_al:LIPIcs.ICLP.2010.64,
  author =	{Fayruzov, Timur and Janssen, Jeroen and Vermeir, Dirk and Cornelis, Chris and De Cock, Martine},
  title =	{{Efficient Solving of Time-dependent Answer Set Programs}},
  booktitle =	{Technical Communications of the 26th International Conference on Logic Programming},
  pages =	{64--73},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-17-0},
  ISSN =	{1868-8969},
  year =	{2010},
  volume =	{7},
  editor =	{Hermenegildo, Manuel and Schaub, Torsten},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICLP.2010.64},
  URN =		{urn:nbn:de:0030-drops-25841},
  doi =		{10.4230/LIPIcs.ICLP.2010.64},
  annote =	{Keywords: Answer set programming, time-dependent programs, gene regulation networks}
}
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