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Authors: Robertas Damasevicius 1 ; Jurgita Kapociute-Dzikiene 2 and Marcin Wozniak 3

Affiliations: 1 Kaunas University of Technology, Lithuania ; 2 Vytautas Magnus University, Lithuania ; 3 Silesian University of Technology, Poland

Keyword(s): Text Mining, Text Phonology, Text Modes, Rhythm, Empirical Mode Decomposition.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems

Abstract: The rhythmicity characteristics of the written text is still an under-researched topic as opposed to the similar research in the speech analysis domain. The paper presents a method for text deconstruction into text modes using Empirical Mode Decomposition (EMD). First, the text is encoded into a numerical sequence using a mapping table. Next, the resulting numerical sequence is decomposed into Intrinsic Mode Functions (IMFs) using EMD. The resulting text modes provide a basis for further analysis of a text as well as specific characteristics of the language of the text itself. The text modes are used further to derive the measures of text complexity (cardinality) and rhythmicity (frequency) as well as the visual representations (scalograms, convograms), which can provide important insights into the structure of the text itself. The application of EMD to text analysis allows to decompose text into basic harmonics, which can be attributed to the structural units of the text such as syl lables, words, verses and stanzas. Higher order harmonics however can be observed only in the rhymed types of the text such as poetry. (More)

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Paper citation in several formats:
Damasevicius, R.; Kapociute-Dzikiene, J. and Wozniak, M. (2017). Towards Rhythmicity Analysis of Text using Empirical Mode Decomposition. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 310-317. DOI: 10.5220/0006586803100317

@conference{kdir17,
author={Robertas Damasevicius. and Jurgita Kapociute{-}Dzikiene. and Marcin Wozniak.},
title={Towards Rhythmicity Analysis of Text using Empirical Mode Decomposition},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={310-317},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006586803100317},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - Towards Rhythmicity Analysis of Text using Empirical Mode Decomposition
SN - 978-989-758-271-4
IS - 2184-3228
AU - Damasevicius, R.
AU - Kapociute-Dzikiene, J.
AU - Wozniak, M.
PY - 2017
SP - 310
EP - 317
DO - 10.5220/0006586803100317
PB - SciTePress