Search Results

Documents authored by Ozaki, Ana


Document
Resource Paper
TØIRoads: A Road Data Model Generation Tool

Authors: Grunde Haraldsson Wesenberg and Ana Ozaki

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2


Abstract
We describe road data models which can represent high level features of a road network such as population, points of interest, and road length/cost and capacity, while abstracting from time and geographic location. Such abstraction allows for a simplified traffic usage and congestion analysis that focus on the high level features. We provide theoretical results regarding mass conservation and sufficient conditions for avoiding congestion within the model. We describe a road data model generation tool, which we call "TØI Roads". We also describe several parameters that can be specified by a TØI Roads user to create graph data that can serve as input for training graph neural networks (or another learning approach that receives graph data as input) for predicting congestion within the model. The road data model generation tool allows, for instance, the study of the effects of population growth and how changes in road capacity can mitigate traffic congestion.

Cite as

Grunde Haraldsson Wesenberg and Ana Ozaki. TØIRoads: A Road Data Model Generation Tool. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 6:1-6:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{wesenberg_et_al:TGDK.2.2.6,
  author =	{Wesenberg, Grunde Haraldsson and Ozaki, Ana},
  title =	{{T{\O}IRoads: A Road Data Model Generation Tool}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{6:1--6:12},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.6},
  URN =		{urn:nbn:de:0030-drops-225901},
  doi =		{10.4230/TGDK.2.2.6},
  annote =	{Keywords: Road Data, Transportation, Graph Neural Networks, Synthetic Dataset Generation}
}
Document
Strong Faithfulness for ELH Ontology Embeddings

Authors: Victor Lacerda, Ana Ozaki, and Ricardo Guimarães

Published in: TGDK, Volume 2, Issue 3 (2024). Transactions on Graph Data and Knowledge, Volume 2, Issue 3


Abstract
Ontology embedding methods are powerful approaches to represent and reason over structured knowledge in various domains. One advantage of ontology embeddings over knowledge graph embeddings is their ability to capture and impose an underlying schema to which the model must conform. Despite advances, most current approaches do not guarantee that the resulting embedding respects the axioms the ontology entails. In this work, we formally prove that normalized ELH has the strong faithfulness property on convex geometric models, which means that there is an embedding that precisely captures the original ontology. We present a region-based geometric model for embedding normalized ELH ontologies into a continuous vector space. To prove strong faithfulness, our construction takes advantage of the fact that normalized ELH has a finite canonical model. We first prove the statement assuming (possibly) non-convex regions, allowing us to keep the required dimensions low. Then, we impose convexity on the regions and show the property still holds. Finally, we consider reasoning tasks on geometric models and analyze the complexity in the class of convex geometric models used for proving strong faithfulness.

Cite as

Victor Lacerda, Ana Ozaki, and Ricardo Guimarães. Strong Faithfulness for ELH Ontology Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 3, pp. 2:1-2:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{lacerda_et_al:TGDK.2.3.2,
  author =	{Lacerda, Victor and Ozaki, Ana and Guimar\~{a}es, Ricardo},
  title =	{{Strong Faithfulness for ELH Ontology Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:29},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.3.2},
  URN =		{urn:nbn:de:0030-drops-225965},
  doi =		{10.4230/TGDK.2.3.2},
  annote =	{Keywords: Knowledge Graph Embeddings, Ontologies, Description Logic}
}
Document
Complete Volume
OASIcs, Volume 99, AIB 2022, Complete Volume

Authors: Camille Bourgaux, Ana Ozaki, and Rafael Peñaloza

Published in: OASIcs, Volume 99, International Research School in Artificial Intelligence in Bergen (AIB 2022)


Abstract
OASIcs, Volume 99, AIB 2022, Complete Volume

Cite as

International Research School in Artificial Intelligence in Bergen (AIB 2022). Open Access Series in Informatics (OASIcs), Volume 99, pp. 1-180, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@Proceedings{bourgaux_et_al:OASIcs.AIB.2022,
  title =	{{OASIcs, Volume 99, AIB 2022, Complete Volume}},
  booktitle =	{International Research School in Artificial Intelligence in Bergen (AIB 2022)},
  pages =	{1--180},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-228-0},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{99},
  editor =	{Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.AIB.2022},
  URN =		{urn:nbn:de:0030-drops-159976},
  doi =		{10.4230/OASIcs.AIB.2022},
  annote =	{Keywords: OASIcs, Volume 99, AIB 2022, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Camille Bourgaux, Ana Ozaki, and Rafael Peñaloza

Published in: OASIcs, Volume 99, International Research School in Artificial Intelligence in Bergen (AIB 2022)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

International Research School in Artificial Intelligence in Bergen (AIB 2022). Open Access Series in Informatics (OASIcs), Volume 99, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{bourgaux_et_al:OASIcs.AIB.2022.0,
  author =	{Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{International Research School in Artificial Intelligence in Bergen (AIB 2022)},
  pages =	{0:i--0:x},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-228-0},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{99},
  editor =	{Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.AIB.2022.0},
  URN =		{urn:nbn:de:0030-drops-159984},
  doi =		{10.4230/OASIcs.AIB.2022.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Paper
Reasoning in Knowledge Graphs (Invited Paper)

Authors: Ricardo Guimarães and Ana Ozaki

Published in: OASIcs, Volume 99, International Research School in Artificial Intelligence in Bergen (AIB 2022)


Abstract
Knowledge Graphs (KGs) are becoming increasingly popular in the industry and academia. They can be represented as labelled graphs conveying structured knowledge in a domain of interest, where nodes and edges are enriched with metaknowledge such as time validity, provenance, language, among others. Once the data is structured as a labelled graph one can apply reasoning techniques to extract relevant and insightful information. We provide an overview of deductive and inductive reasoning approaches for reasoning in KGs.

Cite as

Ricardo Guimarães and Ana Ozaki. Reasoning in Knowledge Graphs (Invited Paper). In International Research School in Artificial Intelligence in Bergen (AIB 2022). Open Access Series in Informatics (OASIcs), Volume 99, pp. 2:1-2:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{guimaraes_et_al:OASIcs.AIB.2022.2,
  author =	{Guimar\~{a}es, Ricardo and Ozaki, Ana},
  title =	{{Reasoning in Knowledge Graphs}},
  booktitle =	{International Research School in Artificial Intelligence in Bergen (AIB 2022)},
  pages =	{2:1--2:31},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-228-0},
  ISSN =	{2190-6807},
  year =	{2022},
  volume =	{99},
  editor =	{Bourgaux, Camille and Ozaki, Ana and Pe\~{n}aloza, Rafael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.AIB.2022.2},
  URN =		{urn:nbn:de:0030-drops-160005},
  doi =		{10.4230/OASIcs.AIB.2022.2},
  annote =	{Keywords: Knowledge Graphs, Description Logics, Knowledge Graph Embeddings}
}
Document
Complete Volume
LIPIcs, Volume 178, TIME 2020, Complete Volume

Authors: Emilio Muñoz-Velasco, Ana Ozaki, and Martin Theobald

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)


Abstract
LIPIcs, Volume 178, TIME 2020, Complete Volume

Cite as

27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 1-292, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@Proceedings{munozvelasco_et_al:LIPIcs.TIME.2020,
  title =	{{LIPIcs, Volume 178, TIME 2020, Complete Volume}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{1--292},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020},
  URN =		{urn:nbn:de:0030-drops-129670},
  doi =		{10.4230/LIPIcs.TIME.2020},
  annote =	{Keywords: LIPIcs, Volume 178, TIME 2020, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Emilio Muñoz-Velasco, Ana Ozaki, and Martin Theobald

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{munozvelasco_et_al:LIPIcs.TIME.2020.0,
  author =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020.0},
  URN =		{urn:nbn:de:0030-drops-129688},
  doi =		{10.4230/LIPIcs.TIME.2020.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Preserving Constraints with the Stable Chase

Authors: David Carral, Markus Krötzsch, Maximilian Marx, Ana Ozaki, and Sebastian Rudolph

Published in: LIPIcs, Volume 98, 21st International Conference on Database Theory (ICDT 2018)


Abstract
Conjunctive query answering over databases with constraints – also known as (tuple-generating) dependencies – is considered a central database task. To this end, several versions of a construction called chase have been described. Given a set Sigma of dependencies, it is interesting to ask which constraints not contained in Sigma that are initially satisfied in a given database instance are preserved when computing a chase over Sigma. Such constraints are an example for the more general class of incidental constraints, which when added to Sigma as new dependencies do not affect certain answers and might even speed up query answering. After formally introducing incidental constraints, we show that deciding incidentality is undecidable for tuple-generating dependencies, even in cases for which query entailment is decidable. For dependency sets with a finite universal model, the core chase can be used to decide incidentality. For the infinite case, we propose the stable chase, which generalises the core chase, and study its relation to incidental constraints.

Cite as

David Carral, Markus Krötzsch, Maximilian Marx, Ana Ozaki, and Sebastian Rudolph. Preserving Constraints with the Stable Chase. In 21st International Conference on Database Theory (ICDT 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 98, pp. 12:1-12:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{carral_et_al:LIPIcs.ICDT.2018.12,
  author =	{Carral, David and Kr\"{o}tzsch, Markus and Marx, Maximilian and Ozaki, Ana and Rudolph, Sebastian},
  title =	{{Preserving Constraints with the Stable Chase}},
  booktitle =	{21st International Conference on Database Theory (ICDT 2018)},
  pages =	{12:1--12:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-063-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{98},
  editor =	{Kimelfeld, Benny and Amsterdamer, Yael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2018.12},
  URN =		{urn:nbn:de:0030-drops-86015},
  doi =		{10.4230/LIPIcs.ICDT.2018.12},
  annote =	{Keywords: Incidental constraints, Tuple-generating dependencies, Infinite core chase, Universal Model, BCQ entailment}
}
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