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Authors: Christian Kahmann ; Andreas Niekler and Gerhard Heyer

Affiliation: Leipzig University, Germany

ISBN: 978-989-758-271-4

Keyword(s): Context Volatility, Semantic Change.

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

Abstract: Terms in diachronic text corpora may exhibit a high degree of semantic dynamics that is only partially captured by the common notion of semantic change. The new measure of context volatility that we propose models the degree by which terms change context in a text collection over time. The computation of context volatility for a word relies on the significance-values of its co-occurrent terms and the corresponding co-occurrence ranks in sequential time spans. We define a baseline and present an efficient computational approach in order to overcome problems related to computational issues in the data structure. Results are evaluated both, on synthetic documents that are used to simulate contextual changes, and a real example based on British newspaper texts. The data and software are avaiable at https://git.informatik.uni-leipzig.de/mam10cip/KDIR.git.

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Paper citation in several formats:
Kahmann, C.; Niekler, A. and Heyer, G. (2017). Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 135-143. DOI: 10.5220/0006574001350143

@conference{kdir17,
author={Christian Kahmann. and Andreas Niekler. and Gerhard Heyer.},
title={Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2017},
pages={135-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006574001350143},
isbn={978-989-758-271-4},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Detecting and Assessing Contextual Change in Diachronic Text Documents using Context Volatility
SN - 978-989-758-271-4
AU - Kahmann, C.
AU - Niekler, A.
AU - Heyer, G.
PY - 2017
SP - 135
EP - 143
DO - 10.5220/0006574001350143

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