3 Search Results for "Chen, Carol"

Document
DOI: 10.4230/LIPIcs.COSIT.2024.6
Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?

Authors: Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Despite the frequent use of sketch maps in assessing environmental knowledge, it remains unclear how and to what degree familiarity impacts sketch map content. In the present study, we assess whether different levels of familiarity relate to differences in the content and spatial accuracy of environmental knowledge depicted in sketch maps drawn for the purpose of route instructions. To this end, we conduct a real-world wayfinding study with 91 participants, all of whom have to walk along a pre-defined route of approximately 2.3km length. Prior to the walk, we collect self-report familiarity ratings from participants for both a set of 15 landmarks and a set of areas we define as hexagons along the route. Once participants finished walking the route, they were asked to sketch a map of the route, specifically a sketch that would enable a person who had never walked the route to follow it. We found that participants unfamiliar with the areas along the route sketched fewer features than familiar people did. Contrary to our expectations, however, we found that landmarks were sketched or not regardless of participants' level of familiarity with the landmarks. We were also surprised that the level of familiarity was not correlated to the accuracy of the sketched order of features along the route, of the position of sketched features in relation to the route, nor to the metric locational accuracy of feature placement on the sketches. These results lead us to conclude that different aspects of feature salience influence whether the features are included on sketch maps, independent of familiarity. They also point to the influence of task context on the content of sketch maps, again independent of familiarity. We propose further studies to more fully explore these ideas.
Cite as

Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos. Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kattenbeck_et_al:LIPIcs.COSIT.2024.6,
  author =	{Kattenbeck, Markus and Montello, Daniel R. and Raubal, Martin and Giannopoulos, Ioannis},
  title =	{{Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{6:1--6:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.6},
  URN =		{urn:nbn:de:0030-drops-208215},
  doi =		{10.4230/LIPIcs.COSIT.2024.6},
  annote =	{Keywords: Familiarity, Spatial Knowledge, Sketch Maps}
}
Document
Position
DOI: 10.4230/TGDK.2.1.5
Standardizing Knowledge Engineering Practices with a Reference Architecture

Authors: Bradley P. Allen and Filip Ilievski

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
Knowledge engineering is the process of creating and maintaining knowledge-producing systems. Throughout the history of computer science and AI, knowledge engineering workflows have been widely used given the importance of high-quality knowledge for reliable intelligent agents. Meanwhile, the scope of knowledge engineering, as apparent from its target tasks and use cases, has been shifting, together with its paradigms such as expert systems, semantic web, and language modeling. The intended use cases and supported user requirements between these paradigms have not been analyzed globally, as new paradigms often satisfy prior pain points while possibly introducing new ones. The recent abstraction of systemic patterns into a boxology provides an opening for aligning the requirements and use cases of knowledge engineering with the systems, components, and software that can satisfy them best, however, this direction has not been explored to date. This paper proposes a vision of harmonizing the best practices in the field of knowledge engineering by leveraging the software engineering methodology of creating reference architectures. We describe how a reference architecture can be iteratively designed and implemented to associate user needs with recurring systemic patterns, building on top of existing knowledge engineering workflows and boxologies. We provide a six-step roadmap that can enable the development of such an architecture, consisting of scope definition, selection of information sources, architectural analysis, synthesis of an architecture based on the information source analysis, evaluation through instantiation, and, ultimately, instantiation into a concrete software architecture. We provide an initial design and outcome of the definition of architectural scope, selection of information sources, and analysis. As the remaining steps of design, evaluation, and instantiation of the architecture are largely use-case specific, we provide a detailed description of their procedures and point to relevant examples. We expect that following through on this vision will lead to well-grounded reference architectures for knowledge engineering, will advance the ongoing initiatives of organizing the neurosymbolic knowledge engineering space, and will build new links to the software architectures and data science communities.
Cite as

Bradley P. Allen and Filip Ilievski. Standardizing Knowledge Engineering Practices with a Reference Architecture. In Special Issue on Trends in Graph Data and Knowledge - Part 2. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 1, pp. 5:1-5:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{allen_et_al:TGDK.2.1.5,
  author =	{Allen, Bradley P. and Ilievski, Filip},
  title =	{{Standardizing Knowledge Engineering Practices with a Reference Architecture}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{5:1--5:23},
  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.2.1.5},
  URN =		{urn:nbn:de:0030-drops-198623},
  doi =		{10.4230/TGDK.2.1.5},
  annote =	{Keywords: knowledge engineering, knowledge graphs, quality attributes, software architectures, sociotechnical systems}
}
Document
DOI: 10.4230/LIPIcs.ITP.2022.30
Formalizing Algorithmic Bounds in the Query Model in EasyCrypt

Authors: Alley Stoughton, Carol Chen, Marco Gaboardi, and Weihao Qu

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

Abstract
We use the EasyCrypt proof assistant to formalize the adversarial approach to proving lower bounds for computational problems in the query model. This is done using a lower bound game between an algorithm and adversary, in which the adversary answers the algorithm’s queries in a way that makes the algorithm issue at least the desired number of queries. A complementary upper bound game is used for proving upper bounds of algorithms; here the adversary incrementally and adaptively realizes an algorithm’s input. We prove a natural connection between the lower and upper bound games, and apply our framework to three computational problems, including searching in an ordered list and comparison-based sorting, giving evidence for the generality of our notion of algorithm and the usefulness of our framework.
Cite as

Alley Stoughton, Carol Chen, Marco Gaboardi, and Weihao Qu. Formalizing Algorithmic Bounds in the Query Model in EasyCrypt. In 13th International Conference on Interactive Theorem Proving (ITP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 237, pp. 30:1-30:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{stoughton_et_al:LIPIcs.ITP.2022.30,
  author =	{Stoughton, Alley and Chen, Carol and Gaboardi, Marco and Qu, Weihao},
  title =	{{Formalizing Algorithmic Bounds in the Query Model in EasyCrypt}},
  booktitle =	{13th International Conference on Interactive Theorem Proving (ITP 2022)},
  pages =	{30:1--30:21},
  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.2022.30},
  URN =		{urn:nbn:de:0030-drops-167399},
  doi =		{10.4230/LIPIcs.ITP.2022.30},
  annote =	{Keywords: query model, lower bound, upper bound, adversary argument, EasyCrypt}
}
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