Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)

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Analysis Graph-Based Data Model For Simple Search Application Using NER Data

Authors
Ade Hodijah1, *, Trisna Gelar1
1Computer and Informatics Engineering, Politeknik Negeri Bandung, Bandung, Indonesia
*Corresponding author. Email: ade.hodijah@polban.ac.id
Corresponding Author
Ade Hodijah
Available Online 17 February 2024.
DOI
10.2991/978-94-6463-364-1_86How to use a DOI?
Keywords
NER; horticultural; Graph Data Modeling
Abstract

Analysis of the seven steps of the Graph Data Modeling approach to obtain application functionality by utilizing the links (relationships) between entities (nodes) of the Named Entity Recognition (NER) entities was the aim of this study. The seven steps have two main models: the Initial and the Refactoring graph. This paper used the NER horticultural dataset to support data requirements in simple search applications with graph-based data storage technology (Neo4j). The domain of applying the NER model was an Indonesian language instructional text document on the sub-topic of horticulture in the context of the cultivation process of fruit trees in Indonesia. Extraction results (NER entities) from horticultural records were stored in Neo4j, and the Cypher query provided by Neo4j was used to support the data search application. Use case scenarios as application functionalities had been successfully tested based on sufficient questions (keywords) for scientific study material. The experimental results showed that the Refactoring graph was faster than the Initial graph. The total number of nodes scanned in the Refactoring graph was almost three times less than in the Initial graph by specifying labels, nodes, and relationships. This paper can be a reference in graph-based modelling.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
Series
Advances in Engineering Research
Publication Date
17 February 2024
ISBN
978-94-6463-364-1
ISSN
2352-5401
DOI
10.2991/978-94-6463-364-1_86How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ade Hodijah
AU  - Trisna Gelar
PY  - 2024
DA  - 2024/02/17
TI  - Analysis Graph-Based Data Model For Simple Search Application Using NER Data
BT  - Proceedings of the International Conference on Applied Science and Technology on Engineering Science 2023 (iCAST-ES 2023)
PB  - Atlantis Press
SP  - 943
EP  - 957
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-364-1_86
DO  - 10.2991/978-94-6463-364-1_86
ID  - Hodijah2024
ER  -