A Systematic Mapping with Bibliometric Analysis on Information Systems Using Ontology and Fuzzy Logic

The ontology-based information systems (IS) development is beneficial for analyzing, conceptual modeling, designing, and re-engineering complex IS to be semantically enriched and suitable for sophisticated reasoning on the IS content. On the other hand, fuzzy theory employment to handle uncertainty and fuzziness in IS becomes a hot topic in different practical domains, such as engineering, IS, computer sciences, etc. As such, ontology- and fuzzy-based IS are being developed. Consequently, there is a need to provide a comprehensive systematic mapping study (SMS) to build a structure on the ontology- and fuzzy-based IS field of interest and to grasp the main ideas. This paper presents findings of SMS, based on the papers extracted from Web of Science and Scopus and employing a bibliometric analysis tool to automate keyword mapping. We conclude this paper by summarizing the previous work and identifying possible research trends, which future investigations can extend. The main finding indicates that ontology and fuzzy logic contribute to ISs by expanding traditional IS to be intelligent IS, which is applicable for solving complex, fuzzy, and semantically rich (ontological) information collection, saving, processing, sharing, and reasoning in different application domains according to users’ needs in various countries.

[1]  Olegas Vasilecas,et al.  Ontology-Based Application for Domain Rules Development , 2010 .

[2]  Olegas Vasilecas,et al.  Application of the Ontology Axioms for the Development of OCL Constraints from PAL Constraints , 2012, Informatica.

[3]  Rafael Valencia-García,et al.  Ontology-driven aspect-based sentiment analysis classification: An infodemiological case study regarding infectious diseases in Latin America , 2020, Future Generation Computer Systems.

[4]  Wolf-Tilo Balke,et al.  Knowledge Representation and the Embodied Mind: Towards a Philosophy and Technology of Personalized Informatics , 2005, Wissensmanagement.

[5]  Wei-Zhi Wu,et al.  Attribute reduction based on evidence theory in incomplete decision systems , 2008, Inf. Sci..

[6]  Enrique Herrera-Viedma,et al.  25years at Knowledge-Based Systems , 2015 .

[7]  Enrique Herrera-Viedma,et al.  Sharing notes: An academic social network based on a personalized fuzzy linguistic recommender system , 2018, Eng. Appl. Artif. Intell..

[8]  Oscar Pastor,et al.  Comparing traditional conceptual modeling with ontology-driven conceptual modeling: An empirical study , 2019, Inf. Syst..

[9]  Witold Pedrycz,et al.  Positive approximation: An accelerator for attribute reduction in rough set theory , 2010, Artif. Intell..

[10]  Gangqiang Zhang,et al.  Cc-reduction in a Fully Fuzzy Information System , 2019, J. Intell. Fuzzy Syst..

[11]  Ron Weber,et al.  On the ontological expressiveness of information systems analysis and design grammars , 1993, Inf. Syst. J..

[12]  Giancarlo Guizzardi,et al.  From reference ontologies to ontology patterns and back , 2017, Data Knowl. Eng..

[13]  Roman Słowiński,et al.  Sequential covering rule induction algorithm for variable consistency rough set approaches , 2011, Inf. Sci..

[14]  Edmundas Kazimieras Zavadskas,et al.  Building Information Modeling (BIM) for Structural Engineering: A Bibliometric Analysis of the Literature , 2019, Advances in Civil Engineering.

[15]  Mahmood Alam,et al.  A comprehensive review of type-2 fuzzy Ontology , 2019, Artificial Intelligence Review.

[16]  Lipika Dey,et al.  Information extraction and imprecise query answering from web documents , 2006, Web Intell. Agent Syst..

[17]  Zongmin Ma,et al.  A survey on fuzzy ontologies for the Semantic Web , 2016, The Knowledge Engineering Review.

[18]  Kai Petersen,et al.  Guidelines for conducting systematic mapping studies in software engineering: An update , 2015, Inf. Softw. Technol..

[19]  Jeffery von Ronne,et al.  Intermediate Representations of Mobile Code , 2008, Informatica.

[20]  Cheng Zhang,et al.  What Do We Know about the Effectiveness of Software Design Patterns? , 2012, IEEE Transactions on Software Engineering.

[21]  Naveen K. Chilamkurti,et al.  An ontology-driven personalized food recommendation in IoT-based healthcare system , 2018, The Journal of Supercomputing.

[22]  Guangji Yu,et al.  Characterizations and uncertainty measurement of a fuzzy information system and related results , 2020, Soft Computing.

[23]  Giancarlo Guizzardi,et al.  TOWARDS A FORMAL METHOD FOR THE TRANSFORMATION OF ONTOLOGY AXIOMS TO APPLICATION DOMAIN RULES , 2009 .

[24]  Junli Li,et al.  Global ontology research progress: a bibliometric analysis , 2015, Aslib J. Inf. Manag..

[25]  Pearl Brereton,et al.  Using mapping studies as the basis for further research - A participant-observer case study , 2011, Inf. Softw. Technol..

[26]  Witold Pedrycz,et al.  Selecting Discrete and Continuous Features Based on Neighborhood Decision Error Minimization , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Jianming Zhan,et al.  A novel decision-making approach based on three-way decisions in fuzzy information systems , 2020, Inf. Sci..

[28]  Diana KALIBATIENĖ,et al.  A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development , 2021, Informatica.

[29]  Masahiro Inuiguchi,et al.  Fuzzy rough sets and multiple-premise gradual decision rules , 2006, Int. J. Approx. Reason..

[30]  Chris Cornelis,et al.  Attribute selection with fuzzy decision reducts , 2010, Inf. Sci..

[31]  Wei-Zhi Wu,et al.  Information structures and uncertainty measures in a fully fuzzy information system , 2018, Int. J. Approx. Reason..

[32]  Carol A Gotway Crawford,et al.  A bibliometric analysis of U.S.-based research on the Behavioral Risk Factor Surveillance System. , 2015, American journal of preventive medicine.

[33]  Abbas Ghaemi Bafghi,et al.  A Systematic Mapping Study on Intrusion Alert Analysis in Intrusion Detection Systems , 2018, ACM Comput. Surv..

[34]  Mauricio Marrone,et al.  Conducting systematic literature reviews and bibliometric analyses , 2019, Australian Journal of Management.

[35]  Ed C. M. Noyons,et al.  Automatic term identification for bibliometric mapping , 2008, Scientometrics.

[36]  Qingguo Li,et al.  A novel approach to predictive analysis using attribute-oriented rough fuzzy sets , 2020, Expert Syst. Appl..

[37]  Lien Fu Lai,et al.  Fuzzy Knowledge Management through Knowledge Engineering and Fuzzy Logic , 2010, J. Convergence Inf. Technol..

[38]  Xiaofeng Liu,et al.  Measures of uncertainty based on Gaussian kernel for a fully fuzzy information system , 2020, Knowl. Based Syst..

[39]  D. Dubois,et al.  ROUGH FUZZY SETS AND FUZZY ROUGH SETS , 1990 .

[40]  Ed C. M. Noyons,et al.  A unified approach to mapping and clustering of bibliometric networks , 2010, J. Informetrics.

[41]  K. Thangavel,et al.  Dimensionality reduction based on rough set theory: A review , 2009, Appl. Soft Comput..

[42]  Ahmad C. Bukhari,et al.  Integration of a secure type-2 fuzzy ontology with a multi-agent platform: A proposal to automate the personalized flight ticket booking domain , 2012, Inf. Sci..

[43]  Marzena Kryszkiewicz,et al.  Rules in Incomplete Information Systems , 1999, Inf. Sci..

[44]  Tore Dybå,et al.  Empirical studies of agile software development: A systematic review , 2008, Inf. Softw. Technol..

[45]  D. Moher,et al.  Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement , 2009, BMJ : British Medical Journal.

[46]  Víctor Hugo Menéndez-Domínguez,et al.  Fuzzy ontologies-based user profiles applied to enhance e-learning activities , 2012, Soft Comput..