Database engineering has been progressed up to the Relational database stage. Fuzzy information administration in databases is a complex process in view of adaptable information nature and heterogeneous database frameworks. Relational Database Management System (RDBMS) can just handle fresh information but cannot handle precise data information. Structured Query Language (SQL) is a very powerful tool but can handle data which is crisp and precise in nature. It is not able to fulfill the requirements for information which is indeterminate, uncertain, inapplicable and imprecise and vague in nature. The goal of this work is to use Fuzzy technique in RDBMS. But, Fuzzy Relational Database Management System (FRDB) requires complex data structures, in most cases, are dependent on the platform in which they are implemented. A solution that involves representing an FRDB using an Ontology as an interface has been defined to overcome this problem. A new Fuzzy Query Ontology is proposed in this dissertation with implementation. The implementation layer, which is responsible for parsing and translating user requests into the corresponding DB implementations in transparent, is required to establish communication between the Ontology and the relational databases management system (RDBMS). This ontology defines a framework for storing fuzzy data by defining those using classes, slots, and instances. An Ontology is an explicit and formal specification of a conceptualization. Ontologies provides a shared understanding of a domain which allows interoperability between semantics.
| Published in |
American Journal of Networks and Communications (Volume 4, Issue 3-1)
This article belongs to the Special Issue Ad Hoc Networks |
| DOI | 10.11648/j.ajnc.s.2015040301.14 |
| Page(s) | 16-21 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Fuzzy, Ontology, Fuzzy Data, Metadata, DBMS Catalog, Fuzzy Knowledge Representation, Ontology, Databases, Database Modeling
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APA Style
Geetanjali tyagi, kumar kaushik, Arnika Jain, Manish Bhardwaj. (2015). Ontology Based Fuzzy Query Execution. American Journal of Networks and Communications, 4(3-1), 16-21. https://doi.org/10.11648/j.ajnc.s.2015040301.14
ACS Style
Geetanjali tyagi; kumar kaushik; Arnika Jain; Manish Bhardwaj. Ontology Based Fuzzy Query Execution. Am. J. Netw. Commun. 2015, 4(3-1), 16-21. doi: 10.11648/j.ajnc.s.2015040301.14
AMA Style
Geetanjali tyagi, kumar kaushik, Arnika Jain, Manish Bhardwaj. Ontology Based Fuzzy Query Execution. Am J Netw Commun. 2015;4(3-1):16-21. doi: 10.11648/j.ajnc.s.2015040301.14
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Download@article{10.11648/j.ajnc.s.2015040301.14,
author = {Geetanjali tyagi and kumar kaushik and Arnika Jain and Manish Bhardwaj},
title = {Ontology Based Fuzzy Query Execution},
journal = {American Journal of Networks and Communications},
volume = {4},
number = {3-1},
pages = {16-21},
doi = {10.11648/j.ajnc.s.2015040301.14},
url = {https://doi.org/10.11648/j.ajnc.s.2015040301.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.s.2015040301.14},
abstract = {Database engineering has been progressed up to the Relational database stage. Fuzzy information administration in databases is a complex process in view of adaptable information nature and heterogeneous database frameworks. Relational Database Management System (RDBMS) can just handle fresh information but cannot handle precise data information. Structured Query Language (SQL) is a very powerful tool but can handle data which is crisp and precise in nature. It is not able to fulfill the requirements for information which is indeterminate, uncertain, inapplicable and imprecise and vague in nature. The goal of this work is to use Fuzzy technique in RDBMS. But, Fuzzy Relational Database Management System (FRDB) requires complex data structures, in most cases, are dependent on the platform in which they are implemented. A solution that involves representing an FRDB using an Ontology as an interface has been defined to overcome this problem. A new Fuzzy Query Ontology is proposed in this dissertation with implementation. The implementation layer, which is responsible for parsing and translating user requests into the corresponding DB implementations in transparent, is required to establish communication between the Ontology and the relational databases management system (RDBMS). This ontology defines a framework for storing fuzzy data by defining those using classes, slots, and instances. An Ontology is an explicit and formal specification of a conceptualization. Ontologies provides a shared understanding of a domain which allows interoperability between semantics.},
year = {2015}
}
TY - JOUR T1 - Ontology Based Fuzzy Query Execution AU - Geetanjali tyagi AU - kumar kaushik AU - Arnika Jain AU - Manish Bhardwaj Y1 - 2015/01/28 PY - 2015 N1 - https://doi.org/10.11648/j.ajnc.s.2015040301.14 DO - 10.11648/j.ajnc.s.2015040301.14 T2 - American Journal of Networks and Communications JF - American Journal of Networks and Communications JO - American Journal of Networks and Communications SP - 16 EP - 21 PB - Science Publishing Group SN - 2326-8964 UR - https://doi.org/10.11648/j.ajnc.s.2015040301.14 AB - Database engineering has been progressed up to the Relational database stage. Fuzzy information administration in databases is a complex process in view of adaptable information nature and heterogeneous database frameworks. Relational Database Management System (RDBMS) can just handle fresh information but cannot handle precise data information. Structured Query Language (SQL) is a very powerful tool but can handle data which is crisp and precise in nature. It is not able to fulfill the requirements for information which is indeterminate, uncertain, inapplicable and imprecise and vague in nature. The goal of this work is to use Fuzzy technique in RDBMS. But, Fuzzy Relational Database Management System (FRDB) requires complex data structures, in most cases, are dependent on the platform in which they are implemented. A solution that involves representing an FRDB using an Ontology as an interface has been defined to overcome this problem. A new Fuzzy Query Ontology is proposed in this dissertation with implementation. The implementation layer, which is responsible for parsing and translating user requests into the corresponding DB implementations in transparent, is required to establish communication between the Ontology and the relational databases management system (RDBMS). This ontology defines a framework for storing fuzzy data by defining those using classes, slots, and instances. An Ontology is an explicit and formal specification of a conceptualization. Ontologies provides a shared understanding of a domain which allows interoperability between semantics. VL - 4 IS - 3-1 ER -
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