Fuzzy Ontology-based Approach for the Requirements Query Imprecision Assessment in Data Warehouse Design Process near Negative Fuzzy Operator

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Author(s)

LARBI Abdelmadjid 1,2,* MALKI Mimoun 3,4 BOUKHALFA Kamel 5

1. Department of Computer Science, DL University, 22000, Sidi Bel Abbes EEDIS Laboratory, DL University SBA; Algeria

2. ENERGARID Laboratory (SimulIA Team), TM University, 08000, Bechar, Algeria

3. Ecole Supérieure en Informatique, Sidi Bel Abbes, 22000, Algeria

4. LabRI-SBA Laboratoty (Laboratoire de Recherche en Informatique de Sidi Bel-Abbes)

5. Information Systems Laboratory (ISL), USTHB, Algiers

* Corresponding author.

DOI: https://doi.org/10.5815/ijitcs.2018.02.03

Received: 8 Nov. 2017 / Revised: 1 Dec. 2017 / Accepted: 7 Dec. 2017 / Published: 8 Feb. 2018

Index Terms

Data warehouses design, requirement expression, decisional system, fuzzy ontology, GLMR Model, imprecision, OLAP Analysis, NEAR- Operator

Abstract

The vagueness in decision-making may be due to ambiguity in the decisional requirements expression. Therefore, in the literature dealing with vagueness in decision systems, studies were concentrated on data vagueness and not on decision requirements. In order to evaluate the expression in decision-making requirements and in order to improve the data warehouses design quality, this paper presents a rigorous fuzzy ontology-based solution. 

Based on the latest Zadeh theory “Ref. [1]”, Authors in “Ref. [2.3]”, propose a solution consisting in using ontologies to provide "an understanding of how the meaning of a proposal can be composed of the meaning of its constituents. One of the limitations of this solution is the fuzziness presence only at the adjective sentence. In some sense, our proposal can be seen as a continuation of that work. We limit our study, in this paper to the “Near negative” operator case. To the best of our knowledge, this case has not been addressed yet in the data warehouse context.

Cite This Paper

LARBI Abdelmadjid, MALKI Mimoun, BOUKHALFA Kamel, "Fuzzy Ontology-based Approach for the Requirements Query Imprecision Assessment in Data Warehouse Design Process near Negative Fuzzy Operator", International Journal of Information Technology and Computer Science(IJITCS), Vol.10, No.2, pp.18-32, 2018. DOI:10.5815/ijitcs.2018.02.03

Reference

[1]L. Zadeh, 2008. Toward human level machine intelligence - is it achievable? The need for a paradigm shift. IEEE Computational Intelligence Magazine 3 (3), 11–22.

[2]C. Martinez-Cruz, J. M. Noguera & M. A. Vila, « Flexible queries on relational databases using fuzzy logic and ontologies», Information Sciences; Page(s): 150–164. (2016) 

[3]C. Martinez-Cruz, I. Blanco and M. Vila, “An Ontology to represent Queries in Fuzzy Relational Databases”, ISDA, ,Page(s): 1317-1322 ISSN : 2164-7143 , 2014 

[4]I. Gam and C. Salinesi, "Analyse des Exigences pour la Conception d'Entrepôts de Données", Informatique des Organisations et Systèmes d'Information et de Décision, Tunisie, pp.1023-1038, 2006   

[5]M. Kumar, A. Gosain and Y. Singh, “Quality-Oriented Requirements Engineering for a Data Warehouse”, ACM SIGSOFT Software Engineering, Volume 36 Issue 5, Pages 1-4, September 2011 

[6]Z. Bellahsene, “Schema Evolution in Data Warehouses”, Knowledge and Information Systems, Springer, Volume 4, Issue 3, pp 283–304, 2002

[7]A. Sabri and L. Kjiri,  “Patterns to analyze requirements of a Decisional Information System”, Journal of Computer Application (IJCA), Special Issue On Software Engineering Databases and EXpert Systems (SEDEXS), Number 2, ISBN: 973-93-80870-26-8, 17 , 2012

[8]N. Tamani, L. Ludovic and R. Daniel, A Fuzzy Ontology for Database Querying with Bipolar Preferences, Intern. Journal of Intelligent Systems, Vol.28 Issue 1, pp 4-36,  2013

[9]N.D. Rodríguez, M.P.  Cuéllar ,J. Lilius and M. D. Calvo-Flores, “A fuzzy ontology for semantic modelling and recognition of human behaviour”, Knowledge-Based Systems Volume 66, August 2014, Pages 46–60, 2014, Elsevier 

[10]T. L. L. Siqueira, C. D. A. Ciferri,V. C. Times and R. R. Ciferri, “Modeling vague spatial data warehouses using the VSCube conceptual model”,  GeoInformatica, Volume 18, Issue 2, pp 313–356, Springer, April 2014  

[11]M. M. Jaber, M. K. Abd Ghani, N. Suryana, M. Aal Mohammed and T. Abbas, “Flexible Data Warehouse Parameters: Toward Building an Integrated Architecture”, International Journal of Computer Theory and Engineering, Vol.7, No. 5, October 2015    

[12]O. Pivert, ‎P. Boscal., “Fuzzy preference queries to relational databases”, Book, World Scientific, 2012

[13]D. Fasel, “Fuzzy DW”, Part of the series Fuzzy Management Methods pp. 43-114, Springer 2014. 

[14]C.-Y. Chiu, H.-C. Ku, I.-T. Kuo & P.-C. Shih, Customer information system using fuzzy query and cluster analysis, Journal of Industrial and Production Engineering, 2014

[15]P.K.Marhavilasab, D.Koulouriotisb, V.Gemeni, Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000–2009, Journal of Loss Prevention in the Process Industries Volume 24, Issue 5, September 2011, Pages 477-523

[16]Garima Thakur, Anjana Gosain, DWEVOLVE: A Requirement Based Framework for Data Warehouse Evolution ACM SIGSOFT Software Engineering Notes Page 1 November 2011 Volume 36 Number 6

[17]Chen-Tung Chen, Hui-Lin Cheng, A comprehensive model for selecting information system project under fuzzy environment, International Journal of Project Management, Volume 27, Issue 4, May 2009, Pages 389-399

[18]Olutayo V.A, Eludire A.A, Traffic Accident Analysis Using Decision Trees and Neural Networks, International Journal of Information Technology and Computer Science(IJITCS), ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online), Vol.6, No.2, Jan. 2014

[19]A. Larbi, M. Malki., K. Boukhalfa., A Survey of Decisional Requirements:  Imprecision study. Proceeding JFSE 2017, ISSN 1613-0073, pp 21-26

[20]Rashmi S, Hanumanthappa M,  Determining the Degree of Knowledge Processing in Semantics through Probabilistic Measures, I.J. Information Technology and Computer Science,2017,7,35-41, 2017, DOI: 10.5815/ijitcs.2017.07.04

[21]Wael K. Hanna, Aziza S.Aseem, M.B.Senousy , Issues and Challenges of User Intent Discovery (UID) during Web Search, I.J. Information Technology and Computer Science, 2015,07,66-76, June 2015, pp66-76, DOI: 10.5815/ijitcs.2015.07.08

[22]Afaf Merazi, Mimoun Malki, SQUIREL: Semantic Querying Interlinked OWL-S traveling Process Models,  International Journal of Information Technology and Computer Science(IJITCS), ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online), Vol.7, No.12, Nov. 2015

[23]M. Golfarelli, S. Rizzi and E. Turricchia, “Modern Software Engineering Methodologies Meet Data Warehouse Design: 4WD”,  Chapter, Data Warehousing and Knowledge Discovery, Volume 6862, pp 66-79,  Springer, 2011 

[24]J. Pardillo and J. Mazón, “Using ontologies for the Design of DWs”, International Journal of Database Management Systems (IJDMS), Vol.3, No.2, May 2011

[25]F Ghozzi, F Ravat, O Teste and G Zurfluh. Méthode de conception d’une base multidimensionnelle contrainte. In Revue des Nouvelles Technologies de l’Information - Entrepôts de Données et l’Analyse en ligne (EDA’05), volume RNTI B-1, pages 51–70. Cépadues éditions, 2005

[26]N. Prakash and Anjana Gosain, “Requirements Driven Data Warehouse Development”, CAiSE Short Paper Proceedings, India, 2005

[27]Oscar Romero and Alberto Abelló, ”A Survey of Multidimensional Modeling Methodologies”, International Journal of Data Warehousing & Mining, 2009

[28]L.Sapir, A. Shmilovici  and  L.  Rokach,  “A methodology for the design of Fuzzy DW”, 4th International IEEE Conference "Intelligent Systems", 2008

[29]D. Boyadzhieva, B. Kolev and N. Netov, “Intuitionistic Fuzzy DW and Some Analytical operations”, Intelligent Systems (IS), IEEE Transactions on Fuzzy Systems, VOL.22, N°.4, August 2014

[30]Tasneem memon ; mian muhammad usman ghani ; nadeem iftikhar , Category of fuzzy operators in SQL, International Conference on Emerging Technologies, 2007. 

[31]Ajay Agarwala, Apeksha Aggarwal, Apoorv Agarwal,  An Approach for Augmenting Selection Operators of SQL Queries using Skyline and Fuzzy-Logic Operators, 7th International Conference on Advances in Computing & Communications, ICACC-2017, 22- 24 August 2017, Cochin, India, Elsevier, Procedia Computer Science 115 (2017) 14–21  

[32]A. Delgado and A. Marotta, “Automating the process of   building flexible Web Warehouses with BPM Systems”, Latin American Computing Conference, 2015

[33]D. Fasel, “Fuzzy Data Warehousing for Performance Measurement Concept and Implementation”, Fuzzy Management Methods pp 43-114, ISBN: 978-3-319-04225-1 (Print) 978-3-319-04226-8, 2014

[34]D. Fasel, “Concept and Implementation of a Fuzzy Data Warehouse”, Univ. of Fribourg; thesis, 2012

[35]S. Khouri, I. Boukhari, L. Bellatreche, E. Sardet, S. Jean and M. Baron, “Ontology-based structured web data warehouses for sustainable interoperability: requirement modeling, design methodology and tool”, Computers in industry; Elsevier (2012)

[36]H. Ghorbel, A. Bahri and R. Bouaziz, “Fuzzy Protégé for fuzzy ontology models”.  Proceeding of 11th International Conference IPC’2009. Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands. 2009

[37]Y. Jiang, Y.Tang, Q.Chen and J.Wang, “Reasoning and change management in modular fuzzy ontologies”. Expert Systems with Applications 38 (11), 13975–13986. 2011

[38]J. M. Mendel, J.Lawry, and L. Zadeh, “Foreword to the special section on computing with words”. IEEE T. Fuzzy Systems 18 (3), 437–440. 2010

[39]F. Bobillo and U. Straccia, “Fuzzy Ontology representation using OWL 2”. International Journal of Approximate Reasoning 52(7), 1073–1094. 2011

[40]JM Mendel, LA Zadeh, E Trillas, R Yager, J Lawry, What computing with words means to me, IEEE Computational Intelligence Magazine, 2010

[41]A.Larbi, M.Malki ; K.Boukhalfa and H.Layachi, “Modeling the Imprecision of Flexible Queries Using  a Fuzzy SQL Language”, 2nd Engineering and New Technologies, ICSENT’13, Tunis, ISBN: 978-9938-12-094-3, 2013

[42]A.Larbi., M.Malki, A.Ben Ahmed, K.Boukhalfa, « Modélisation de préférences à base de croyance du décideur », Tunis, Proceeding ASD 2017, pp 11-17

[43]S. Jean, OntoQL, un langage d'exploitation des bases de données à base ontologique, Thèse,  Laboratoire d'Informatique Scientifique et Industrielle, Poitiers, France, 2007 

[44]A.Larbi, M.Malki, B.Seddiki, I.Larbi, “A semi-automatic solution for XML query response enrichment using a terminological domain ontology”, Proceeding ICCES '17, Istanbul, Turkey, ACM New York, NY, USA 2017, ISBN: 978-1-4503-5309-0 ; doi: 10.1145/3129186.3131941