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Authors: Iwona Dudek and Jean-Yves Blaise

Affiliation: UMR CNRS/MCC 3495 MAP, France

Keyword(s): Visualisation, Knowledge Modelling, Sensemaking, Spatio-Temporal Data, Textual Content, Narratives.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Context Discovery ; Data Analytics ; Data Engineering ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems ; Visual Data Mining and Data Visualization

Abstract: Supporting knowledge discovery through visual means is a hot research topic in the field of visual analytics in general, and a key issue in the analysis of textual data sets. In that context, the StorylineViz study aims at developing a generic approach to narrative analysis, supporting the identification of significant patterns inside textual data, and ultimately knowledge discovery and sensemaking. It builds on a text segmentation procedure through which sequences of situations are extracted. A situation is defined by a quadruplet of components: actors, space, time and motion. The approach aims at facilitating visual reasoning on the structure, rhythm, patterns and variations of heterogeneous texts in order to enable comparative analysis, and to summarise how the space/time/actors/motion components are organised inside a given narrative. It encompasses issues that are rooted in Information Sciences - visual analytics, knowledge representation – and issues that more closely relate to Digital Humanities – comparative methods and analytical reasoning on textual content, support in teaching and learning, cultural mediation. (More)

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Paper citation in several formats:
Dudek, I. and Blaise, J. (2016). StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 21-32. DOI: 10.5220/0006034600210032

@conference{kdir16,
author={Iwona Dudek. and Jean{-}Yves Blaise.},
title={StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR},
year={2016},
pages={21-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006034600210032},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR
TI - StorylineViz: A [Space, Time, Actors, Motion] Segmentation Method for Visual Text Exploration
SN - 978-989-758-203-5
IS - 2184-3228
AU - Dudek, I.
AU - Blaise, J.
PY - 2016
SP - 21
EP - 32
DO - 10.5220/0006034600210032
PB - SciTePress