Zobrazit v EDS

Enhancing database query interpretation: a comparative analysis of semantic parsing models.

Uloženo v:
Podrobná bibliografie
Název: Enhancing database query interpretation: a comparative analysis of semantic parsing models.
Autoři: Keswani, Gunjan, Chandak, Manoj B.
Zdroj: International Journal of Informatics & Communication Technology (IJ-ICT); Aug2025, Vol. 14 Issue 2, p467-477, 11p
Témata: PROCESS capability, INFORMATION retrieval, DATABASES, ELECTRONIC data processing, DATABASE design
Abstrakt: The rapid proliferation of NoSQL databases in various domains necessitates effective parsing models for interpreting NoSQL queries, a fundamental aspect often overlooked in database management research. This paper addresses the critical need for a comprehensive understanding of existing semantic parsing models tailored for NoSQL query interpretation. We identify inherent issues in current models, such as limitations in precision, accuracy, and scalability, alongside challenges in deployment complexity and processing delays. This review is pivotal, shedding light on the intricacies and inefficiencies of existing systems, thereby guiding future advancements in NoSQL database querying. This methodical comparison of these models across key performance metrics-precision, accuracy, recall, delay, deployment complexity, and scalability-reveals significant disparities and areas for improvement. By evaluating these models against both individual and combined parameters, we identify the most effective methods currently available. The impact of this work is far-reaching, providing a foundational framework for developing more robust, efficient, and scalable parsing models. This, in turn, has the potential to revolutionize the way NoSQL databases are queried and managed, offering significant improvements in data retrieval and analysis. Through this paper, we aim to bridge the gap between theoretical model development and practical database management, paving the way for enhanced data processing capabilities in diverse NoSQL database applications. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Informatics & Communication Technology (IJ-ICT) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
Popis
Abstrakt:The rapid proliferation of NoSQL databases in various domains necessitates effective parsing models for interpreting NoSQL queries, a fundamental aspect often overlooked in database management research. This paper addresses the critical need for a comprehensive understanding of existing semantic parsing models tailored for NoSQL query interpretation. We identify inherent issues in current models, such as limitations in precision, accuracy, and scalability, alongside challenges in deployment complexity and processing delays. This review is pivotal, shedding light on the intricacies and inefficiencies of existing systems, thereby guiding future advancements in NoSQL database querying. This methodical comparison of these models across key performance metrics-precision, accuracy, recall, delay, deployment complexity, and scalability-reveals significant disparities and areas for improvement. By evaluating these models against both individual and combined parameters, we identify the most effective methods currently available. The impact of this work is far-reaching, providing a foundational framework for developing more robust, efficient, and scalable parsing models. This, in turn, has the potential to revolutionize the way NoSQL databases are queried and managed, offering significant improvements in data retrieval and analysis. Through this paper, we aim to bridge the gap between theoretical model development and practical database management, paving the way for enhanced data processing capabilities in diverse NoSQL database applications. [ABSTRACT FROM AUTHOR]
ISSN:22528776
DOI:10.11591/ijict.v14i2.pp467-477