2 Search Results for "Cavazza, Marc"

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DOI: 10.4230/TGDK.1.1.6
Towards Ordinal Data Science

Authors: Gerd Stumme, Dominik Dürrschnabel, and Tom Hanika

Published in: TGDK, Volume 1, Issue 1 (2023): Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 1, Issue 1

Abstract
Order is one of the main instruments to measure the relationship between objects in (empirical) data. However, compared to methods that use numerical properties of objects, the amount of ordinal methods developed is rather small. One reason for this is the limited availability of computational resources in the last century that would have been required for ordinal computations. Another reason - particularly important for this line of research - is that order-based methods are often seen as too mathematically rigorous for applying them to real-world data. In this paper, we will therefore discuss different means for measuring and ‘calculating’ with ordinal structures - a specific class of directed graphs - and show how to infer knowledge from them. Our aim is to establish Ordinal Data Science as a fundamentally new research agenda. Besides cross-fertilization with other cornerstone machine learning and knowledge representation methods, a broad range of disciplines will benefit from this endeavor, including, psychology, sociology, economics, web science, knowledge engineering, scientometrics.
Cite as

Gerd Stumme, Dominik Dürrschnabel, and Tom Hanika. Towards Ordinal Data Science. In Special Issue on Trends in Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 1, Issue 1, pp. 6:1-6:39, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Article{stumme_et_al:TGDK.1.1.6,
  author =	{Stumme, Gerd and D\"{u}rrschnabel, Dominik and Hanika, Tom},
  title =	{{Towards Ordinal Data Science}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{6:1--6:39},
  ISSN =	{2942-7517},
  year =	{2023},
  volume =	{1},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.1.1.6},
  URN =		{urn:nbn:de:0030-drops-194801},
  doi =		{10.4230/TGDK.1.1.6},
  annote =	{Keywords: Order relation, data science, relational theory of measurement, metric learning, general algebra, lattices, factorization, approximations and heuristics, factor analysis, visualization, browsing, explainability}
}
Document
DOI: 10.4230/OASIcs.CMN.2014.42
Towards Empathic Neurofeedback for Interactive Storytelling

Authors: Marc Cavazza, Gabor Aranyi, Fred Charles, Julie Porteous, Stephen Gilroy, Ilana Klovatch, Gilan Jackont, Eyal Soreq, Nimrod Jakob Keynan, Avihay Cohen, Gal Raz, and Talma Hendler

Published in: OASIcs, Volume 41, 2014 Workshop on Computational Models of Narrative

Abstract
Interactive Narrative is a form of digital entertainment based on AI techniques which support narrative generation and user interaction. Despite recent progress in the field, there is still a lack of unified models integrating narrative generation, user response and interaction. This paper addresses this issue by revisiting existing Interactive Narrative paradigms, granting explicit status to users' disposition towards story characters. We introduce a novel Brain-Computer Interface (BCI) design, which attempts to capture empathy for the main character in a way that is compatible with filmic theories of emotion. Results from two experimental studies with a fully-implemented system demonstrate the effectiveness of a neurofeedback-based approach, showing that subjects can successfully modulate their emotional support for a character who is confronted with challenging situations. A preliminary fMRI analysis also shows activation during user interaction, in regions of the brain associated with emotional control.
Cite as

Marc Cavazza, Gabor Aranyi, Fred Charles, Julie Porteous, Stephen Gilroy, Ilana Klovatch, Gilan Jackont, Eyal Soreq, Nimrod Jakob Keynan, Avihay Cohen, Gal Raz, and Talma Hendler. Towards Empathic Neurofeedback for Interactive Storytelling. In 2014 Workshop on Computational Models of Narrative. Open Access Series in Informatics (OASIcs), Volume 41, pp. 42-60, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

Copy BibTex To Clipboard

@InProceedings{cavazza_et_al:OASIcs.CMN.2014.42,
  author =	{Cavazza, Marc and Aranyi, Gabor and Charles, Fred and Porteous, Julie and Gilroy, Stephen and Klovatch, Ilana and Jackont, Gilan and Soreq, Eyal and Keynan, Nimrod Jakob and Cohen, Avihay and Raz, Gal and Hendler, Talma},
  title =	{{Towards Empathic Neurofeedback for Interactive Storytelling}},
  booktitle =	{2014 Workshop on Computational Models of Narrative},
  pages =	{42--60},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-71-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{41},
  editor =	{Finlayson, Mark A. and Meister, Jan Christoph and Bruneau, Emile G.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2014.42},
  URN =		{urn:nbn:de:0030-drops-46442},
  doi =		{10.4230/OASIcs.CMN.2014.42},
  annote =	{Keywords: brain-computer interfaces, neurofeedback, interactive narrative, affective computing}
}
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