LINGUISTIC SUMMARIES IN EVALUATING ELEMENTARY CONDITIONS AND THEIR APPLICATION IN SOFTWARE ENVIRONMENT

Authors

  • Pavol Sojka Ing. Pavol Sojka, University of Economics in Bratislava, Faculty of Economic Informatics, Department of Applied Informatics

DOI:

https://doi.org/10.12955/pns.v2.159

Keywords:

fuzzy logic, linguistic summaries, degree of membership, computational intelligence, web application, databases

Abstract

Data users are generally interested in two types of aggregated information: summarization of the selected attribute(s) for all considered entities and retrieval and evaluation of entities by the requirements posed on the relevant attributes. Less statistically literate users (e.g., domain experts) and the business intelligence strategic dashboards can benefit from linguistic summarization, i.e. a summary like most customers are middle-aged can be understood immediately. Evaluation of the mandatory and optional requirements of the structure P1 and most of the other posed predicates should be satisfied beneficial for analytical business intelligence dashboards and search engines in general. This work formalizes the integration of the aforementioned quantified summaries and quantified evaluation into the concept of database queries to empower their flexibility by, e.g., the nested quantified query conditions on hierarchical data structures. Later in our work, we adapted our research into practical application. We created a software environment for evaluating data based on a dataset retrieved from The Statistical Office of the Slovak republic. These datasets are aimed mainly on landscape characteristics like altitude, area sizes of towns and villages, and similar parameters. Based on user's preferences, our system recommends the most suitable place for holidays to spend on.

References

Beliakov, G., Pradera, A., Calvo Sánchez, T. (2007). Aggregation Functions: A Guide for Practitioners. Springer-Verlag, Berlin, Heidelberg.

Boran, F.E., Akay, D., Yager, R.R. (2016). An overview of methods for linguistic summarization with fuzzy sets. Expert Systems with Applications, 61, 356–377.

Bosc, P., Pivert, O. (2012). On four noncommutative fuzzy connectives and their axiomatization. Fuzzy Sets and Systems, 202, 42–60.

Bosc, P., Hadjali, A., Pivert, O. (2007). Weakening of fuzzy relational queries: and absolute proximity relation-based approach. Mathware and Soft Computing, 14, 35–55.

Bosc, P., Hadjali, A., Pivert, O. (2008). Empty versus overabundant answers to flexible relational queries. Fuzzy Sets and Systems, 159, 1450–1467.

Bosc, P., Brando, C., Hadjali, A., Jaudoin, H., Pivert, O. (2009). Semantic proximity between queries and the empty answer problem. In: Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, Lisbon, pp. 259–264.

Dubois, D., Prade, H. (2004). On the use of aggregation operations in information fusion processes. Fuzzy Sets and Systems, 142, 143–161.

Dubois, D., Prade, H. (2012). Fundamentals of Fuzzy Sets. Springer Science & Business Media.

Dujmović, J. (2007). Continuous Preference Logic for System Evaluation. In: IEEE Transactions on Fuzzy Systems, vol. 15, no. 6, pp. 1082-1099, Dec. 2007, doi: 10.1109/TFUZZ.2007.902041.

Farnadi, G., Bach, S.H., Moens, M.F., Getoor, L. & De Cock, M. (2014). Extending PSL with fuzzy quantifiers. In: Proceedings of the 13th AAAI Conference on Statistical Relational AI (AAAIWS'14-13). AAAI Press, 35–37.

Hájek, P. (2013). Meta Mathematics of Fuzzy Logic. Springer-Science+Business media, B.V.

Hudec, M. (2009). An approach to fuzzy database querying, analysis and realization. Computer Science and Information Systems, 6, 127–140.

Hudec, M. (2016). Fuzziness in Information Systems – How to Deal with Crisp and Fuzzy Data in Selection, Classification, and Summarization. Springer, Cham.

Hudec, M., Mesiar, R. (2020). The axiomatization of asymmetric disjunction and conjunction. Information Fusion, 53, 165–173.

Hudec, M., Vučetić, M. (2015). Some issues of fuzzy querying in relational databases. Kybern, 51, 994–1022.

Hudec, M., Vučetić, M. (2019). Aggregation of fuzzy conformances. In: 10th International Summer School on Aggregation Operators, AGOP 2019, Olomouc, Czech Republic.

Hudec, M., Bednárová, E., Holzinger, A. (2018). Augmenting statistical data dissemination by short quantified sentences of natural language. Journal of Official Statistics, 34, 981–1010.

Kacprzyk, J., Pasi, G., Vojtáš, P., Zadrożny, S. (2000). Fuzzy querying: issues and perspectives. Kybernetika, 36, 605–616.

Keefe, R. (2000). Theories of Vagueness. Cambridge University Press, Cambridge.

Kacprzyk, J., Yager, R. R., & Zadrozny, S. (2002). Fuzzy Linguistic Summaries of Databases for an Efficient Business Data Analysis and Decision Support. In Knowledge Discovery for Business Information Systems (pp. 129–152). Kluwer Academic Publishers. https://doi.org/10.1007/0-306-46991-x_6

Kacprzyk, J., Zadrożny, S. (2001). SQLf and FQUERY for Access. Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), 2001, pp. 2464-2469 vol.4, doi: 10.1109/NAFIPS.2001.944459.

Kacprzyk, J., Zadrożny, S. (2013). Comprehensiveness of Linguistic Data Summaries: A Crucial Role of Protoforms. In Computational Intelligence in Intelligent Data Analysis (pp. 207–221). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-32378-2_14

Kacprzyk, J., Zadrożny, S. (2013). Compound bipolar queries: combining bipolar queries and queries with fuzzy linguistic quantifiers. Proceedings of the 8th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-13). https://doi.org/10.2991/eusflat.2013.125

Klement, E.P., Mesiar, R., Pap, E. (2005). Triangular norms: basic notions and properties. In: Klement, E.P., Mesiar, R. (Eds.), Logical, Algebraic, Analytic, and Probabilistic Aspects of Triangular Norms. Elsevier, Amsterdam, pp. 17–60.

Rakovská, E., & Hudec, M. (2019). Two approaches for the computational model for software usability in practice. Advances in Intelligent Systems and Computing, 191-202. doi:10.1007/978-3-030-18058-4_15

Schield, M. (2011). Statistical literacy: a new mission for data producers. Statistical Journal of the IAOS, 27, 173–183.

Skowron, A., Jankowski, A., Swiniarski, R.W. (2015). Foundations of rough sets. In: Kacprzyk, J., Pedrycz, W. (Eds.), Handbook of Computational Intelligence. Springer, Berlin, Heidelberg, pp. 331–348.

Smits, G., Pivert, O., Hadjali, A. (2014). Fuzzy cardinalities as a basis to cooperative answering. In: Pivert, O., Zadrożny, S. (Eds.), Flexible Approaches in Data, Information and Knowledge Management. Studies in Computational Intelligence, Vol. 497. Springer, Cham, pp. 261–289.

Sojka, P., Hudec, M., Švaňa, M. (2020). Linguistic Summaries in Evaluating Elementary Conditions, Summarizing Data and Managing Nested Queries. In Informatica : An International Journal. Vilnius : Vilnius University. Vol. 4, 31, 841-856.

Tamani N., Liétard L., Rocacher D. (2011) Bipolar SQLf: A Flexible Querying Language for Relational Databases. In: Christiansen H., De Tré G., Yazici A., Zadrozny S., Andreasen T., Larsen H.L. (eds) Flexible Query Answering Systems. FQAS 2011. Lecture Notes in Computer Science, vol 7022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24764-4_41

Wang, T-C., Lee, L.H-D., Chen, C-M. (2007). Intelligent queries based on fuzzy set theory and SQL. In: 39th Joint Conference on Information Science, Salt Lake City, pp. 1426–1432.

Xu, J., Zhou, X. (2011). Fuzzy-Like Multiple Objective Decision Making. In Studies in Fuzziness and Soft Computing. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-16895-6

Yager, R.R., Kacprzyk, J. (2012). The ordered weighted averaging operators: theory and applications. Springer Science & Business Media.

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Published

2021-10-24

How to Cite

Sojka, P. . (2021). LINGUISTIC SUMMARIES IN EVALUATING ELEMENTARY CONDITIONS AND THEIR APPLICATION IN SOFTWARE ENVIRONMENT. Proceedings of CBU in Natural Sciences and ICT, 2, 93-99. https://doi.org/10.12955/pns.v2.159
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