28 Search Results for "Reynolds, Mark"


Volume

LIPIcs, Volume 206

28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

TIME 2021, September 27-29, 2021, Klagenfurt, Austria

Editors: Carlo Combi, Johann Eder, and Mark Reynolds

Document
Two-Dimensional Kripke Semantics I: Presheaves

Authors: G. A. Kavvos

Published in: LIPIcs, Volume 299, 9th International Conference on Formal Structures for Computation and Deduction (FSCD 2024)


Abstract
The study of modal logic has witnessed tremendous development following the introduction of Kripke semantics. However, recent developments in programming languages and type theory have led to a second way of studying modalities, namely through their categorical semantics. We show how the two correspond.

Cite as

G. A. Kavvos. Two-Dimensional Kripke Semantics I: Presheaves. In 9th International Conference on Formal Structures for Computation and Deduction (FSCD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 299, pp. 14:1-14:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{kavvos:LIPIcs.FSCD.2024.14,
  author =	{Kavvos, G. A.},
  title =	{{Two-Dimensional Kripke Semantics I: Presheaves}},
  booktitle =	{9th International Conference on Formal Structures for Computation and Deduction (FSCD 2024)},
  pages =	{14:1--14:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-323-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{299},
  editor =	{Rehof, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSCD.2024.14},
  URN =		{urn:nbn:de:0030-drops-203438},
  doi =		{10.4230/LIPIcs.FSCD.2024.14},
  annote =	{Keywords: modal logic, categorical semantics, Kripke semantics, duality, open maps}
}
Document
Track B: Automata, Logic, Semantics, and Theory of Programming
Identifying Tractable Quantified Temporal Constraints Within Ord-Horn

Authors: Jakub Rydval, Žaneta Semanišinová, and Michał Wrona

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)


Abstract
The constraint satisfaction problem, parameterized by a relational structure, provides a general framework for expressing computational decision problems. Already the restriction to the class of all finite structures forms an interesting microcosm on its own, but to express decision problems in temporal reasoning one has to take a step beyond the finite-domain realm. An important class of templates used in this context are temporal structures, i.e., structures over ℚ whose relations are first-order definable using the usual countable dense linear order without endpoints. In the standard setting, which allows only existential quantification over input variables, the complexity of finite and temporal constraints has been fully classified. In the quantified setting, i.e., when one also allows universal quantifiers, there is only a handful of partial classification results and many concrete cases of unknown complexity. This paper presents a significant progress towards understanding the complexity of the quantified constraint satisfaction problem for temporal structures. We provide a complexity dichotomy for quantified constraints over the Ord-Horn fragment, which played an important role in understanding the complexity of constraints both over temporal structures and in Allen’s interval algebra. We show that all problems under consideration are in P or coNP-hard. In particular, we determine the complexity of the quantified constraint satisfaction problem for (ℚ;x = y⇒ x ≥ z), hereby settling a question open for more than ten years.

Cite as

Jakub Rydval, Žaneta Semanišinová, and Michał Wrona. Identifying Tractable Quantified Temporal Constraints Within Ord-Horn. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 151:1-151:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@InProceedings{rydval_et_al:LIPIcs.ICALP.2024.151,
  author =	{Rydval, Jakub and Semani\v{s}inov\'{a}, \v{Z}aneta and Wrona, Micha{\l}},
  title =	{{Identifying Tractable Quantified Temporal Constraints Within Ord-Horn}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{151:1--151:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.151},
  URN =		{urn:nbn:de:0030-drops-202944},
  doi =		{10.4230/LIPIcs.ICALP.2024.151},
  annote =	{Keywords: constraint satisfaction problems, quantifiers, dichotomy, temporal reasoning, Ord-Horn}
}
Document
Position
Grounding Stream Reasoning Research

Authors: Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1


Abstract
In the last decade, there has been a growing interest in applying AI technologies to implement complex data analytics over data streams. To this end, researchers in various fields have been organising a yearly event called the "Stream Reasoning Workshop" to share perspectives, challenges, and experiences around this topic. In this paper, the previous organisers of the workshops and other community members provide a summary of the main research results that have been discussed during the first six editions of the event. These results can be categorised into four main research areas: The first is concerned with the technological challenges related to handling large data streams. The second area aims at adapting and extending existing semantic technologies to data streams. The third and fourth areas focus on how to implement reasoning techniques, either considering deductive or inductive techniques, to extract new and valuable knowledge from the data in the stream. This summary is written not only to provide a crystallisation of the field, but also to point out distinctive traits of the stream reasoning community. Moreover, it also provides a foundation for future research by enumerating a list of use cases and open challenges, to stimulate others to join this exciting research area.

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Pieter Bonte, Jean-Paul Calbimonte, Daniel de Leng, Daniele Dell'Aglio, Emanuele Della Valle, Thomas Eiter, Federico Giannini, Fredrik Heintz, Konstantin Schekotihin, Danh Le-Phuoc, Alessandra Mileo, Patrik Schneider, Riccardo Tommasini, Jacopo Urbani, and Giacomo Ziffer. Grounding Stream Reasoning Research. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 2:1-2:47, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{bonte_et_al:TGDK.2.1.2,
  author =	{Bonte, Pieter and Calbimonte, Jean-Paul and de Leng, Daniel and Dell'Aglio, Daniele and Della Valle, Emanuele and Eiter, Thomas and Giannini, Federico and Heintz, Fredrik and Schekotihin, Konstantin and Le-Phuoc, Danh and Mileo, Alessandra and Schneider, Patrik and Tommasini, Riccardo and Urbani, Jacopo and Ziffer, Giacomo},
  title =	{{Grounding Stream Reasoning Research}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:47},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.2},
  URN =		{urn:nbn:de:0030-drops-198597},
  doi =		{10.4230/TGDK.2.1.2},
  annote =	{Keywords: Stream Reasoning, Stream Processing, RDF streams, Streaming Linked Data, Continuous query processing, Temporal Logics, High-performance computing, Databases}
}
Document
Survey
Semantic Web: Past, Present, and Future

Authors: Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal

Published in: TGDK, Volume 2, Issue 1 (2024): Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge, Volume 2, Issue 1


Abstract
Ever since the vision was formulated, the Semantic Web has inspired many generations of innovations. Semantic technologies have been used to share vast amounts of information on the Web, enhance them with semantics to give them meaning, and enable inference and reasoning on them. Throughout the years, semantic technologies, and in particular knowledge graphs, have been used in search engines, data integration, enterprise settings, and machine learning. In this paper, we recap the classical concepts and foundations of the Semantic Web as well as modern and recent concepts and applications, building upon these foundations. The classical topics we cover include knowledge representation, creating and validating knowledge on the Web, reasoning and linking, and distributed querying. We enhance this classical view of the so-called "Semantic Web Layer Cake" with an update of recent concepts that include provenance, security and trust, as well as a discussion of practical impacts from industry-led contributions. We conclude with an outlook on the future directions of the Semantic Web. This is a living document. If you like to contribute, please contact the first author and visit: https://github.com/ascherp/semantic-web-primer

Cite as

Ansgar Scherp, Gerd Groener, Petr Škoda, Katja Hose, and Maria-Esther Vidal. Semantic Web: Past, Present, and Future. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 3:1-3:37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


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@Article{scherp_et_al:TGDK.2.1.3,
  author =	{Scherp, Ansgar and Groener, Gerd and \v{S}koda, Petr and Hose, Katja and Vidal, Maria-Esther},
  title =	{{Semantic Web: Past, Present, and Future}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{3:1--3:37},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.1.3},
  URN =		{urn:nbn:de:0030-drops-198607},
  doi =		{10.4230/TGDK.2.1.3},
  annote =	{Keywords: Linked Open Data, Semantic Web Graphs, Knowledge Graphs}
}
Document
Seventeen Provers Under the Hammer

Authors: Martin Desharnais, Petar Vukmirović, Jasmin Blanchette, and Makarius Wenzel

Published in: LIPIcs, Volume 237, 13th International Conference on Interactive Theorem Proving (ITP 2022)


Abstract
One of the main success stories of automatic theorem provers has been their integration into proof assistants. Such integrations, or "hammers," increase proof automation and hence user productivity. In this paper, we use Isabelle/HOL’s Sledgehammer tool to find out how useful modern provers are at proving formulas in higher-order logic. Our evaluation follows in the steps of Böhme and Nipkow’s Judgment Day study from 2010, but instead of three provers we use 17, including SMT solvers and higher-order provers. Our work offers an alternative yardstick for comparing modern provers, next to the benchmarks and competitions emerging from the TPTP World and SMT-LIB.

Cite as

Martin Desharnais, Petar Vukmirović, Jasmin Blanchette, and Makarius Wenzel. Seventeen Provers Under the Hammer. In 13th International Conference on Interactive Theorem Proving (ITP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 237, pp. 8:1-8:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{desharnais_et_al:LIPIcs.ITP.2022.8,
  author =	{Desharnais, Martin and Vukmirovi\'{c}, Petar and Blanchette, Jasmin and Wenzel, Makarius},
  title =	{{Seventeen Provers Under the Hammer}},
  booktitle =	{13th International Conference on Interactive Theorem Proving (ITP 2022)},
  pages =	{8:1--8:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-252-5},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{237},
  editor =	{Andronick, June and de Moura, Leonardo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITP.2022.8},
  URN =		{urn:nbn:de:0030-drops-167178},
  doi =		{10.4230/LIPIcs.ITP.2022.8},
  annote =	{Keywords: Automatic theorem proving, interactive theorem proving, proof assistants}
}
Document
Complete Volume
LIPIcs, Volume 206, TIME 2021, Complete Volume

Authors: Carlo Combi, Johann Eder, and Mark Reynolds

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
LIPIcs, Volume 206, TIME 2021, Complete Volume

Cite as

28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 1-244, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@Proceedings{combi_et_al:LIPIcs.TIME.2021,
  title =	{{LIPIcs, Volume 206, TIME 2021, Complete Volume}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{1--244},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021},
  URN =		{urn:nbn:de:0030-drops-147755},
  doi =		{10.4230/LIPIcs.TIME.2021},
  annote =	{Keywords: LIPIcs, Volume 206, TIME 2021, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Carlo Combi, Johann Eder, and Mark Reynolds

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


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

Cite as

28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{combi_et_al:LIPIcs.TIME.2021.0,
  author =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.0},
  URN =		{urn:nbn:de:0030-drops-147761},
  doi =		{10.4230/LIPIcs.TIME.2021.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning (Invited Talk)

Authors: Luke Hunsberger and Roberto Posenato

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
Since Simple Temporal Networks (STNs) were first introduced in 1991, there have been numerous theoretic and algorithmic advances that have made them practical for a wide variety of applications. However, the presentation of most of the important advances have been scattered across numerous conference papers and journal articles. As a result, it is too easy for even experienced researchers to be unaware of results that could positively impact their work. In this talk we review the most important results about STNs for researchers in Artificial Intelligence who are interested in incorporating the management of time and temporal constraints into their projects.

Cite as

Luke Hunsberger and Roberto Posenato. Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning (Invited Talk). In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 1:1-1:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{hunsberger_et_al:LIPIcs.TIME.2021.1,
  author =	{Hunsberger, Luke and Posenato, Roberto},
  title =	{{Simple Temporal Networks: A Practical Foundation for Temporal Representation and Reasoning}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{1:1--1:5},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.1},
  URN =		{urn:nbn:de:0030-drops-147770},
  doi =		{10.4230/LIPIcs.TIME.2021.1},
  annote =	{Keywords: Simple Temporal Networks, Consistency Checking, Restoring Consistency, Dispatchability, Temporal Decoupling Problem}
}
Document
Invited Talk
Extreme-Scale Model-Based Time Series Management with ModelarDB (Invited Talk)

Authors: Torben Bach Pedersen

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
To monitor critical industrial devices such as wind turbines, high quality sensors sampled at a high frequency are increasingly used. Current technology does not handle these extreme-scale time series well [Søren Kejser Jensen et al., 2017], so only simple aggregates are traditionally stored, removing outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing extreme-scale time series that approximates the time series values using mathematical functions (models) and stores only model coefficients rather than data values. Compression is done both for individual time series and for correlated groups of time series. The keynote will present concepts, techniques, and algorithms from model-based time series management and our implementation of these in the open source Time Series Management System (TSMS) ModelarDB[Søren Kejser Jensen et al., 2018; Søren Kejser Jensen et al., 2019; Søren Kejser Jensen et al., 2021] . Furthermore, it will present our experimental evaluation of ModelarDB on extreme-scale real-world time series, which shows that that compared to widely used Big Data formats, ModelarDB provides up to 14× faster ingestion due to high compression, 113× better compression due to its adaptability, 573× faster aggregatation by using models, and close to linear scale-out scalability. ModelarDB is being commercialized by the spin-out company ModelarData.

Cite as

Torben Bach Pedersen. Extreme-Scale Model-Based Time Series Management with ModelarDB (Invited Talk). In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 2:1-2:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{pedersen:LIPIcs.TIME.2021.2,
  author =	{Pedersen, Torben Bach},
  title =	{{Extreme-Scale Model-Based Time Series Management with ModelarDB}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{2:1--2:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.2},
  URN =		{urn:nbn:de:0030-drops-147785},
  doi =		{10.4230/LIPIcs.TIME.2021.2},
  annote =	{Keywords: Model-based storage, approximate query processing, time series management, extreme-scale data}
}
Document
Invited Talk
Kernel Machines in Time (Invited Talk)

Authors: Johan Suykens

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
Kernel machines is a powerful class of models in machine learning with solid foundations and many existing application fields. The scope of this talk is kernel machines in time with a main focus on least squares support vector machines, and other related methods such as kernel principal component analysis and kernel spectral clustering. For dynamical systems modelling different possible input-output and state space model structures will be discussed. Applications will be shown on electricity load forecasting and temperature prediction in weather forecasting. Approximate closed-form solutions can be given to ordinary and partial differential equations. Kernel spectral clustering applications to identifying customer profiles, pollution modelling and detecting topological changes in time-series of bridges will be shown. Finally, new synergies between kernel machines and deep learning will be presented, leading for example to generative kernel machines, with new insights on disentangled representations, explainability and latent space exploration. Application of these models will be illustrated on out-of-distribution detection of time-series data.

Cite as

Johan Suykens. Kernel Machines in Time (Invited Talk). In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, p. 3:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{suykens:LIPIcs.TIME.2021.3,
  author =	{Suykens, Johan},
  title =	{{Kernel Machines in Time}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{3:1--3:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.3},
  URN =		{urn:nbn:de:0030-drops-147791},
  doi =		{10.4230/LIPIcs.TIME.2021.3},
  annote =	{Keywords: SVM, Time series analysis}
}
Document
Panel Description
Temporal Big Data Analytics: New Frontiers for Big Data Analytics Research (Panel Description)

Authors: Alfredo Cuzzocrea

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
Big data analytics is an emerging research area with many sophisticated contributions in the actual literature. Big data analytics aims at discovering actionable knowledge from large amounts of big data repositories, based on several approaches that integrate foundations of a wide spectrum of disciplines, ranging from data mining to machine learning and artificial intelligence. Among the concrete innovative topics of big data analytics, temporal big data analytics covers a first-class role and it is attracting the attention of larger and larger communities of academic and industrial researchers. Basically, temporal big data analytics aims at modeling, capturing and analyzing temporal aspects of big data during analytics phase, including specialized tasks such as big data versioning over time, building temporal relations among ad-hoc big data structures (such as nodes of big graphs) and temporal queries over big data. It is worth to notice that temporal big data analytics research is characterized by several open challenges, which range from foundations, including temporal big data representation and processing, to applications, including smart cities and bio-informatics tools. Inspired by these considerations, this paper focuses on models, paradigms, techniques and future challenges of temporal big data analytics, by reporting on state-of-the-art results as well as emerging trends, with also criticisms on future work that we should expect from the community.

Cite as

Alfredo Cuzzocrea. Temporal Big Data Analytics: New Frontiers for Big Data Analytics Research (Panel Description). In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 4:1-4:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{cuzzocrea:LIPIcs.TIME.2021.4,
  author =	{Cuzzocrea, Alfredo},
  title =	{{Temporal Big Data Analytics: New Frontiers for Big Data Analytics Research}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{4:1--4:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.4},
  URN =		{urn:nbn:de:0030-drops-147804},
  doi =		{10.4230/LIPIcs.TIME.2021.4},
  annote =	{Keywords: Big Data Analytics, Big Data Management, Temporal Big Data Analytics, Temporal Big Data Management}
}
Document
Model Checking of Stream Processing Pipelines

Authors: Alexis Bédard and Sylvain Hallé

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
Event stream processing (ESP) is the application of a computation to a set of input sequences of arbitrary data objects, called "events", in order to produce other sequences of data objects. In recent years, a large number of ESP systems have been developed; however, none of them is easily amenable to a formal verification of properties on their execution. In this paper, we show how stream processing pipelines built with an existing ESP library called BeepBeep 3 can be exported as a Kripke structure for the NuXmv model checker. This makes it possible to formally verify properties on these pipelines, and opens the way to the use of such pipelines directly within a model checker as an extension of its specification language.

Cite as

Alexis Bédard and Sylvain Hallé. Model Checking of Stream Processing Pipelines. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 5:1-5:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{bedard_et_al:LIPIcs.TIME.2021.5,
  author =	{B\'{e}dard, Alexis and Hall\'{e}, Sylvain},
  title =	{{Model Checking of Stream Processing Pipelines}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{5:1--5:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.5},
  URN =		{urn:nbn:de:0030-drops-147819},
  doi =		{10.4230/LIPIcs.TIME.2021.5},
  annote =	{Keywords: stream processing, model checking}
}
Document
Investigation of Database Models for Evolving Graphs

Authors: Alexandros Spitalas, Anastasios Gounaris, Kostas Tsichlas, and Andreas Kosmatopoulos

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
We deal with the efficient implementation of storage models for time-varying graphs. To this end, we present an improved approach for the HiNode vertex-centric model based on MongoDB. This approach, apart from its inherent space optimality, exhibits significant improvements in global query execution times, which is the most challenging query type for entity-centric approaches. Not only significant speedups are achieved but more expensive queries can be executed as well, when compared to an implementation based on Cassandra due to the capability to exploit indices to a larger extent and benefit from in-database query processing.

Cite as

Alexandros Spitalas, Anastasios Gounaris, Kostas Tsichlas, and Andreas Kosmatopoulos. Investigation of Database Models for Evolving Graphs. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 6:1-6:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{spitalas_et_al:LIPIcs.TIME.2021.6,
  author =	{Spitalas, Alexandros and Gounaris, Anastasios and Tsichlas, Kostas and Kosmatopoulos, Andreas},
  title =	{{Investigation of Database Models for Evolving Graphs}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{6:1--6:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.6},
  URN =		{urn:nbn:de:0030-drops-147821},
  doi =		{10.4230/LIPIcs.TIME.2021.6},
  annote =	{Keywords: Temporal Graphs, Indexing}
}
Document
Interval Temporal Random Forests with an Application to COVID-19 Diagnosis

Authors: Federico Manzella, Giovanni Pagliarini, Guido Sciavicco, and Ionel Eduard Stan

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)


Abstract
Symbolic learning is the logic-based approach to machine learning. The mission of symbolic learning is to provide algorithms and methodologies to extract logical information from data and express it in an interpretable way. In the context of temporal data, interval temporal logic has been recently proposed as a suitable tool for symbolic learning, specifically via the design of an interval temporal logic decision tree extraction algorithm. Building on it, we study here its natural generalization to interval temporal random forests, mimicking the corresponding schema at the propositional level. Interval temporal random forests turn out to be a very performing multivariate time series classification method, which, despite the introduction of a functional component, are still logically interpretable to some extent. We apply this method to the problem of diagnosing COVID-19 based on the time series that emerge from cough and breath recording of positive versus negative subjects. Our experiment show that our models achieve very high accuracies and sensitivities, often superior to those achieved by classical methods on the same data. Although other recent approaches to the same problem (based on different and more numerous data) show even better statistical results, our solution is the first logic-based, interpretable, and explainable one.

Cite as

Federico Manzella, Giovanni Pagliarini, Guido Sciavicco, and Ionel Eduard Stan. Interval Temporal Random Forests with an Application to COVID-19 Diagnosis. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{manzella_et_al:LIPIcs.TIME.2021.7,
  author =	{Manzella, Federico and Pagliarini, Giovanni and Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{Interval Temporal Random Forests with an Application to COVID-19 Diagnosis}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{7:1--7:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.7},
  URN =		{urn:nbn:de:0030-drops-147837},
  doi =		{10.4230/LIPIcs.TIME.2021.7},
  annote =	{Keywords: Interval temporal logic, decision trees, random forests, sound-based diagnosis}
}
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