3 Search Results for "Matthews, Brian"

Document
Research
DOI: 10.4230/TGDK.3.3.4
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

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

Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.
Cite as

Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
DOI: 10.4230/LIPIcs.SAT.2022.2
A Comprehensive Study of k-Portfolios of Recent SAT Solvers

Authors: Jakob Bach, Ashlin Iser, and Klemens Böhm

Published in: LIPIcs, Volume 236, 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)

Abstract
Hard combinatorial problems such as propositional satisfiability are ubiquitous. The holy grail are solution methods that show good performance on all problem instances. However, new approaches emerge regularly, some of which are complementary to existing solvers in that they only run faster on some instances but not on many others. While portfolios, i.e., sets of solvers, have been touted as useful, putting together such portfolios also needs to be efficient. In particular, it remains an open question how well portfolios can exploit the complementarity of solvers. This paper features a comprehensive analysis of portfolios of recent SAT solvers, the ones from the SAT Competitions 2020 and 2021. We determine optimal portfolios with exact and approximate approaches and study the impact of portfolio size k on performance. We also investigate how effective off-the-shelf prediction models are for instance-specific solver recommendations. One result is that the portfolios found with an approximate approach are as good as the optimal solution in practice. We also observe that marginal returns decrease very quickly with larger k, and our prediction models do not give way to better performance beyond very small portfolio sizes.
Cite as

Jakob Bach, Ashlin Iser, and Klemens Böhm. A Comprehensive Study of k-Portfolios of Recent SAT Solvers. In 25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 236, pp. 2:1-2:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{bach_et_al:LIPIcs.SAT.2022.2,
  author =	{Bach, Jakob and Iser, Ashlin and B\"{o}hm, Klemens},
  title =	{{A Comprehensive Study of k-Portfolios of Recent SAT Solvers}},
  booktitle =	{25th International Conference on Theory and Applications of Satisfiability Testing (SAT 2022)},
  pages =	{2:1--2:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-242-6},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{236},
  editor =	{Meel, Kuldeep S. and Strichman, Ofer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2022.2},
  URN =		{urn:nbn:de:0030-drops-166767},
  doi =		{10.4230/LIPIcs.SAT.2022.2},
  annote =	{Keywords: Propositional satisfiability, solver portfolios, runtime prediction, machine learning, integer programming}
}
Document
DOI: 10.4230/DagSemProc.05271.11
Security and Trust Issues in Semantic Grids

Authors: Daniel Olmedilla, Omer F. Rana, Brian Matthews, and Wolfgang Nejdl

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

Abstract
Grid computing allows sharing of services and resources accross institutions. However, current Grid security mechanisms for authentication and authorization are too rigid and they lack the ability to determine how ``trustworthy'' the result obtained from a specific provider is likely to be. This paper describes the different facets associated to Trust and identifies the need for Trust Management approaches in the context of Virtual Organizations lifecycle and resource access control in the Grid.
Cite as

Daniel Olmedilla, Omer F. Rana, Brian Matthews, and Wolfgang Nejdl. Security and Trust Issues in Semantic Grids. In Semantic Grid: The Convergence of Technologies. Dagstuhl Seminar Proceedings, Volume 5271, pp. 1-11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{olmedilla_et_al:DagSemProc.05271.11,
  author =	{Olmedilla, Daniel and Rana, Omer F. and Matthews, Brian and Nejdl, Wolfgang},
  title =	{{Security and Trust Issues in Semantic Grids}},
  booktitle =	{Semantic Grid: The Convergence of Technologies},
  pages =	{1--11},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  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.05271.11},
  URN =		{urn:nbn:de:0030-drops-4081},
  doi =		{10.4230/DagSemProc.05271.11},
  annote =	{Keywords: Trust, Security, Policies, Safety, Reputation, VO Lifecycle}
}
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