research-article

Fuzzy Query Model of the Business Resources Based on Cloud Service Platform

Authors:

Qi-Shi WuAuthors Info & Claims

CSAE '18: Proceedings of the 2nd International Conference on Computer Science and Application Engineering

Article No.: 141, Pages 1 - 5

https://doi.org/10.1145/3207677.3278082

Published: 22 October 2018 Publication History

Abstract

In the cloud1 service platform environment, due to the ambiguity and uncertainty of the users' thoughts and business resources, the existing accurate query method cannot handle this problem. Therefore, in response to this problem, this paper proposes a fuzzy query model of business resources based on cloud service platform. The model is first constructed according to the fuzzy theory, then the fuzzy condition is transformed into the precise condition, finally based on which the query is executed and the query result is returned to meet the users' diversified query requirements. Through experimental research, the model proposed in this paper has good feasibility and effectiveness.

References

[1]

C. Baun, M. Kunze, and J. Nimis, et al. 2011. Cloud computing: web-based dynamic IT services. Springer-Verlag, Berlin Heidelberg, 6--8.

Digital Library

[2]

L. Wang, D. Chen, and Y. Hu, et al. 2013. Towards enabling cyberinfrastructure as a service in clouds. Comput. Electr. Eng., 39(2013), 3--14.

Digital Library

[3]

Y. Yu, LF. Sun, SY. and Wang, et al. 2016. Data security model for industrial chain collaborative SaaS platform. Computer Integrated Manufacturing Systems, 22,12 (2016), 2911--2919.

[4]

Y. Yu, LF. Sun, and YH. Ma. 2017. Access control model for attribute-based cloud manufacturing collaboration platform. Computer Integrated Manufacturing Systems, 23, 1 (2017), 196--202.

[5]

Y. Yu, LF. Sun, and YH. Ma. 2016. Multi-tenant form customization technology for collaborative cloud service platform in industrial chain. Computer Integrated Manufacturing Systems, 22, 9 (2016), 2235--2244.

[6]

V. Tahani. 1977. A conceptual framework for fuzzy querying processing: a step toward very intelligent databases systems. Information Processing & Management, 13(1977), 289--303.

[7]

LA. Zadeh. 1965. Fuzzy Sets. Information and Control, 8 (1965), 338--353.

[8]

SM. Chen, and WT. Jong. 1997. Fuzzy query translation for relational database systems. IEEE Transactions on Systems, Man, and Cybernetics, 27, 4 (1997), 714.

Digital Library

[9]

ZM. Ma, and L. Yan. 2007. Generalization of strategies for fuzzy query translation in classical relational database. Information & Software Technology, 49, 2 (2007), 172--180.

Digital Library

[10]

DZ. Kang, BW. Xu, and JJ. Lu. 2008. Extended fuzzy description logics with comparisons between fuzzy membership degrees. Journal of Software, 19, 10 (2008), 2498--2507.

[11]

YH. Li, BW. Xu, and JJ. Lu. 2008. Reasoning with general terminological axioms in fuzzy description logic FALCN. Journal of Software, 19, 3 (2008), 594--604.

[12]

P. Bosc, and O. Pivert. 1995. SQLf: a relational database language for fuzzy querying. IEEE Transactions on Fuzzy Systems, 3, 1 (1995), 1--17.

Digital Library

[13]

RX. Li, and SB. Su. 2012. Fuzzy query based on xml element and correlation. In Proceeding of the Fourth International Conference on Computational and Information Sciences. IEEE Computer Society, Washington, D.C., 282--285.

Digital Library

[14]

A. Castelltort, and T. Martin. 2017. Handling Scalable Approximate Queries over NoSQL Graph Databases: Cypherf and the Fuzzy4S Framework. Fuzzy Sets & Systems, 5, 40 (2017), 1--29.

[15]

I. Benali-Sougui, MS. Hidri, and A. Grissa-Touzi. 2016. No-FSQL: A Graph-based Fuzzy NoSQL Querying Model. International Journal of Fuzzy System Applications, 5, 2 (2016), 54--63.

Digital Library

[16]

O. Pivert, G. Smits, and V. Thion. 2015. Expression and efficient processing of fuzzy queries in a graph database context. In Proceeding of the 2015 IEEE International Conference on Fuzzy Systems. IEEE Computer Society, Washington, D.C., 1--8.

[17]

H.J Zimmermann. 2011. Fuzzy Set Theory and Its Applications (4nd. ed.). World Book Inc, Chicago, 5--100.

[18]

F. Herrera, E. Herrera-Viedma, and L. Martinez. 2008. A fuzzy linguistic methodology to deal with unbalance linguistic term sets. IEEE Transactions on Fuzzy Systems, 16, 2 (2008), 354--370.

Digital Library

[19]

O. Alhabashneh, R. Iqbal, and F. Doctor, et al. 2017. Fuzzy rule based profiling approach for enterprise information seeking and retrieval. Information Sciences, 394--395 (2017), 18--37.

[20]

BPB. Kantor. 1981. The Logic of weighted Queries. IEEE Transactions on Systems Man & Cybernetics, 11, 12 (1981), 816--821.

[21]

YC. Zhang, H. Wang, and Xl. Ye. 2009. Fuzzy SQL Queries with Weights Based on Fuzzy Logic Conjunctions. In Proceeding of the 2009 WRI Global Congress on Intelligent Systems, IEEE Computer Society, Washington, D.C., 470--473.

Digital Library

[22]

K. Nowacka, SZ, Zny, and J. Kacprzyk. 2008. A new fuzzy logic based information retrieval model. In Proceeding of the 12th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, Springer, Berlin Heidelberg, 1749--1756.

[23]

J. Feng, G. Li, and J. Wang. 2011. Finding top-k answers in keyword search over relational databases using tuple units. IEEE Trans. Knowl. Data Eng., 23(2011), 1781--1794.

Digital Library

[24]

Southwest Jiaotong University. 2012. Cloud service platform for automotive industry chain. URL: http://www.autosaas.cn (125.69.67.34: 10000).

Cited By

Yu YSun LWang S(2022)Multiparty Dynamic Data Integration Scheme of Industrial Chain Collaboration Platform in Mobile Computing EnvironmentWireless Communications & Mobile Computing10.1155/2022/15506682022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/1550668

Index Terms

Fuzzy Query Model of the Business Resources Based on Cloud Service Platform
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing
      1. Query representation

Recommendations

Fuzzy Query Based on XML Element and Correlation
ICCIS '12: Proceedings of the 2012 Fourth International Conference on Computational and Information Sciences

A new approach based on XML element and correlation was proposed to reflect users' fuzzy query intention. Based on the fuzzy sets theory, a fuzzy extension of XPath query expression was proposed, which can be expressed exploiting fuzzy predicates. Then ...
A Knowledge-Based Approach for Answering Fuzzy Queries over Relational Databases
KES '08: Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II

Users often have vague or imprecise ideas when searching the database. Thus, they might like to issue fuzzy queries for possibly retrieving. Based on fuzzy sets theory and the knowledge base related to the application domain, this paper proposes an ...
Database Skeleton and Its Application to Fuzzy Query Translation

This paper treats the problem of fuzzy query translation using the concept of database skeleton. An imprecise, or fuzzy, query is represented by a query graph, which can be analyzed for translatability with respect to a given database skeleton. The ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

CSAE '18: Proceedings of the 2nd International Conference on Computer Science and Application Engineering

October 2018

1083 pages

ISBN:9781450365123

DOI:10.1145/3207677

Conference Chair:
Ali Emrouznejad,
Program Chair:
Zhihong Qian

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

the National Key R&D Plan of China

Conference

CSAE '18

CSAE '18: The 2nd International Conference on Computer Science and Application Engineering

October 22 - 24, 2018

Hohhot, China

Acceptance Rates

CSAE '18 Paper Acceptance Rate 189 of 383 submissions, 49%;

Overall Acceptance Rate 368 of 770 submissions, 48%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
51
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Yu YSun LWang S(2022)Multiparty Dynamic Data Integration Scheme of Industrial Chain Collaboration Platform in Mobile Computing EnvironmentWireless Communications & Mobile Computing10.1155/2022/15506682022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/1550668

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten