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Author: Edgars Rencis

Affiliation: Institute of Mathematics and Computer Science, University of Latvia, 29 Raina blvd., Riga, LV-1459 and Latvia

Keyword(s): Semistar Ontologies, Query Language, Information Retrieval, Query Translation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Software Development ; Symbolic Systems

Abstract: The time necessary for the doubling of medical knowledge is rapidly decreasing. In such circumstances, it is of utmost importance for the information retrieval process to be rapid, convenient and straightforward. However, it often lacks at least one of these properties. Several obstacles prohibit domain experts extracting knowledge from their databases without involving the third party in the form of IT professionals. The main limitation is usually the complexity of querying languages and tools. This paper proposes the approach of using a keywords-containing natural language for querying the database and exploiting the system that could automatically translate such queries to already existing target language that has an efficient implementation upon the database. The querying process is based on data conforming to a Semistar data ontology that has proven to be a very easily perceptible data structure for domain experts. Over time, the system can learn from the user actions, thus maki ng the translation more accurate and the querying – more straightforward. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Rencis, E. (2019). User Experience-based Information Retrieval from Semistar Data Ontologies. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 419-426. DOI: 10.5220/0008345004190426

@conference{kdir19,
author={Edgars Rencis},
title={User Experience-based Information Retrieval from Semistar Data Ontologies},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR},
year={2019},
pages={419-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008345004190426},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR
TI - User Experience-based Information Retrieval from Semistar Data Ontologies
SN - 978-989-758-382-7
IS - 2184-3228
AU - Rencis, E.
PY - 2019
SP - 419
EP - 426
DO - 10.5220/0008345004190426
PB - SciTePress