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Authors: Hua Guo and Kecheng Liu

Affiliation: Informatics Research Centre, University of Reading, Reading and U.K.

ISBN: 978-989-758-372-8

Keyword(s): Ontology Graph, NLP, Knowledge Graph, Decision Support Systems, Semantic Composition, Neural-symbolic Integration.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Natural Language Interfaces to Intelligent Systems ; Strategic Decision Support Systems

Abstract: In the context of the development of AI algorithms in natural language processing, tremendous progress has been made in knowledge abstraction and semantic reasoning. However, for answering the questions with complex logic, AI system is still in an early stage. Hierarchical ontology graph is proposed to establish analysis threads for the complex question in order to facilitate AI system to further support in business decision making. The study of selecting the appropriate corpora is intended to improve the data asset management of enterprises.

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Paper citation in several formats:
Guo, H. and Liu, K. (2019). Hierarchical Ontology Graph for Solving Semantic Issues in Decision Support Systems.In Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-372-8, pages 483-487. DOI: 10.5220/0007769904830487

@conference{iceis19,
author={Hua Guo. and Kecheng Liu.},
title={Hierarchical Ontology Graph for Solving Semantic Issues in Decision Support Systems},
booktitle={Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2019},
pages={483-487},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007769904830487},
isbn={978-989-758-372-8},
}

TY - CONF

JO - Proceedings of the 21st International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Hierarchical Ontology Graph for Solving Semantic Issues in Decision Support Systems
SN - 978-989-758-372-8
AU - Guo, H.
AU - Liu, K.
PY - 2019
SP - 483
EP - 487
DO - 10.5220/0007769904830487

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