User Experience-based Information Retrieval from Semistar Data Ontologies

Edgars Rencis

2019

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 making the translation more accurate and the querying – more straightforward.

Paper Citation

in Harvard Style

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) - Volume 1: KDIR; ISBN 978-989-758-382-7, SciTePress, pages 419-426. DOI: 10.5220/0008345004190426

in Bibtex Style

@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) - Volume 1: KDIR},
year={2019},
pages={419-426},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008345004190426},
isbn={978-989-758-382-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - Volume 1: KDIR
TI - User Experience-based Information Retrieval from Semistar Data Ontologies
SN - 978-989-758-382-7
AU - Rencis E.
PY - 2019
SP - 419
EP - 426
DO - 10.5220/0008345004190426
PB - SciTePress