A design of computational fuzzy set-based semantics for extracting linguistic summaries
Email:
nducdu@utc.edu.vn
Từ khóa:
linguistic summary, hedge algebras, fuzzy set, computational semantics, multi-semantic structure
Tóm tắt
Linguistic summarization is to extract a set of summary sentences in the form of natural language, so-called linguistic summaries, from numeric data. The extracted linguistic summaries should be compact and diverse, and have a validity measure greater than a given threshold, so genetic algorithms are applied to extract such linguistic summaries. Besides, the interpretability of linguistic summary content is considered in recent studies in such a way that enlarged hedge algebras are applied to generate multi-semantic structures for linguistic words of linguistic variables ensuring the interpretability of the content of the linguistic summaries. However, the membership function of computational fuzzy-set-based semantics of linguistic words is usually in the shape of trapezoid. In this paper, a membership function of the form S function is applied to improve the quality of extracted linguistic summaries. Besides, the applied algorithm is parallelized to reduce running time. The experimental results with the creep dataset have demonstrated the effectiveness of the proposed methodTài liệu tham khảo
[1]. R. R. Yager, A new approach to the summarization of data, Information Sciences, 28 (1982) 69-86). https://doi.org/10.1016/0020-0255(82)90033-0
[2]. J. Kacprzyk, R. R. Yager, S. Zadrożny, A fuzzy logic based approach to linguistic summaries of databases, International Journal of Applied Mathematics and Computer Science, 10 (2000) (813-834).
[3]. J. Kacprzyk, S. Zadrożny, Linguistic database summaries and their protoforms: towards natural language based knowledge discovery tools, Information Sciences, 173 (2005) 281-304. https://doi.org/10.1016/j.ins.2005.03.002
[4]. C. A. D. Díaz, R. B. Pérez, E. V. Morales, Using Linguistic Data Summarization in the study of creep data for the design of new steels, in Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on,160-165. https://doi.org/10.1109/ISDA.2011.6121648
[5]. T. Altintop, R. R. Yager, D. Akay, F. E. Boran, M. Ünal, Fuzzy Linguistic Summarization with Genetic Algorithm: An Application with Operational and Financial Healthcare Data, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 25 (2017) 599-620. https://doi.org/10.1142/S021848851750026X
[6]. R. J. Almeida, M.-J. Lesot, B. Bouchon-Meunier, U. Kaymak, G. Moyse, Linguistic summaries of categorical time series for septic shock patient data, Fuzz-IEEE 2013-IEEE International Conference on Fuzzy Systems, Hyderabad, India. IEEE, (2013), 1-8. https://doi.org/10.1109/FUZZ-IEEE.2013.6622581
[7]. J. Kacprzyk R. R. Yager, Linguistic summaries of data using fuzzy logic, International Journal of General System, 30 (2001) 133-154. https://doi.org/10.1080/03081070108960702
[8]. M. D. Peláez-Aguilera, M. Espinilla, M. R. Fernández Olmo, J. Medina, Fuzzy linguistic protoforms to summarize heart rate streams of patients with ischemic heart disease, Complexity, 2019 (2019) 1-11. https://doi.org/10.1155/2019/2694126
[9]. A. Duraj, P. S. Szczepaniak, L. Chomatek, Intelligent Detection of Information Outliers Using Linguistic Summaries with Non-monotonic Quantifiers, International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, (2020) 787-799. https://doi.org/10.1007/978-3-030-50153-2_58
[10]. A. Jain, M. Popescu, J. Keller, M. Rantz, B. Markway, Linguistic summarization of in-home sensor data, Journal of biomedical informatics, 96 (2019) 103240. https://doi.org/10.1016/j.jbi.2019.103240
[11]. A. Wilbik, I. Vanderfeesten, D. Bergmans, S. Heines, W. van Mook, Linguistic summaries for compliance analysis of a glucose management clinical protocol, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), (2018) 1-7. https://doi.org/10.1109/FUZZ-IEEE.2018.8491449
[12]. F. E. Boran, D. Akay, A generic method for the evaluation of interval type-2 fuzzy linguistic summaries, IEEE transactions on cybernetics, 44 (2013) 1632-1645. https://doi.org/10.1109/TCYB.2013.2291272
[13]. C. Donis-Diaz, R. Bello, J. Kacprzyk, Linguistic data summarization using an enhanced genetic algorithm, Technical Transactions – Automatic Control, 2013 (2013) 3-12.
[14]. C. Donis-Diaz, A. Muro, R. Bello-Pérez, E. V. Morales, A hybrid model of genetic algorithm with local search to discover linguistic data summaries from creep data, Expert Systems with Applications, 41 (2014) 2035-2042. https://doi.org/10.1016/j.eswa.2013.09.002
[15]. C. H. Nguyen, T. L. Pham, T. N. Nguyen, C. H. Ho, T. A. Nguyen, The linguistic summarization and the interpretability, scalability of fuzzy representations of multilevel semantic structures of word-domains, Microprocessors and Microsystems, 81 (2021) 103641. https://doi.org/10.1016/j.micpro.2020.103641
[16]. C. H. Nguyen, T. S. Tran, D. P. Pham, Modeling of a semantics core of linguistic terms based on an extension of hedge algebra semantics and its application, Knowledge-Based Systems, 67 (2014) 244-262. https://doi.org/10.1016/j.knosys.2014.04.047
[17]. T. L. Pham, C. H. Nguyen, D. P. Pham, Extracting an optimal set of linguistic summaries using genetic algorithm combined with greedy strategy, Journal on Information Technologies & Communications, 2020 (2020) 75-87. https://doi.org/10.32913/mic-ict-research.v2020.n2.954
[18]. D. P. Pham, T. L. Pham, X. T. Tran, A fuzzinness parameter optimization method to extract the optimal set of linguistic summaries from numeric data, TNU Journal of Science and Technology, 229 (2024) 49-57. https://doi.org/10.34238/tnu-jst.9824
[19]. V. T. Hoang, D. D. Nguyen, C. H. Nguyen, A Method to design semantic of linguistics based on the enlarged hedge algebra and applied to building FRBS for solving regression, Journal on Information Technologies & Communications, 38 (2017) 51-57 (In Vietnamese).
[20]. D. D. Nguyen, D. P. Pham, D. V. Pham, D. T. Nguyen, A design method of computational semantics of linguistic words for fuzzy rule-based classifier, Journal on Information Technologies & Communications, 2020 (2020) 9-18 (In Vietnamese). https://doi.org/10.32913/mic-ict-research-vn.v2020.n1.914
[21]. D. D Nguyen, A method for designing fuzzy rule-based classifier using S-function based fuzzy set guarantee interpretability, Transport and Communications Science Journal, 75 (2014) 1335-1347 (In Vietnamese). https://doi.org/10.47869/tcsj.75.3.2
[22]. A. Tarski, A. Mostowski, R. Robinson, Undecidable Theories. North-Holland, 1953.
[23]. J. Kennedy, R. C. Eberhart, Particle Swarm Optimization, Proceedings of the IEEE International Conference on Neural Networks, Piscataway, New Jersey. IEEE Service Center, (1995) 1942-1948.
[2]. J. Kacprzyk, R. R. Yager, S. Zadrożny, A fuzzy logic based approach to linguistic summaries of databases, International Journal of Applied Mathematics and Computer Science, 10 (2000) (813-834).
[3]. J. Kacprzyk, S. Zadrożny, Linguistic database summaries and their protoforms: towards natural language based knowledge discovery tools, Information Sciences, 173 (2005) 281-304. https://doi.org/10.1016/j.ins.2005.03.002
[4]. C. A. D. Díaz, R. B. Pérez, E. V. Morales, Using Linguistic Data Summarization in the study of creep data for the design of new steels, in Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on,160-165. https://doi.org/10.1109/ISDA.2011.6121648
[5]. T. Altintop, R. R. Yager, D. Akay, F. E. Boran, M. Ünal, Fuzzy Linguistic Summarization with Genetic Algorithm: An Application with Operational and Financial Healthcare Data, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 25 (2017) 599-620. https://doi.org/10.1142/S021848851750026X
[6]. R. J. Almeida, M.-J. Lesot, B. Bouchon-Meunier, U. Kaymak, G. Moyse, Linguistic summaries of categorical time series for septic shock patient data, Fuzz-IEEE 2013-IEEE International Conference on Fuzzy Systems, Hyderabad, India. IEEE, (2013), 1-8. https://doi.org/10.1109/FUZZ-IEEE.2013.6622581
[7]. J. Kacprzyk R. R. Yager, Linguistic summaries of data using fuzzy logic, International Journal of General System, 30 (2001) 133-154. https://doi.org/10.1080/03081070108960702
[8]. M. D. Peláez-Aguilera, M. Espinilla, M. R. Fernández Olmo, J. Medina, Fuzzy linguistic protoforms to summarize heart rate streams of patients with ischemic heart disease, Complexity, 2019 (2019) 1-11. https://doi.org/10.1155/2019/2694126
[9]. A. Duraj, P. S. Szczepaniak, L. Chomatek, Intelligent Detection of Information Outliers Using Linguistic Summaries with Non-monotonic Quantifiers, International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, (2020) 787-799. https://doi.org/10.1007/978-3-030-50153-2_58
[10]. A. Jain, M. Popescu, J. Keller, M. Rantz, B. Markway, Linguistic summarization of in-home sensor data, Journal of biomedical informatics, 96 (2019) 103240. https://doi.org/10.1016/j.jbi.2019.103240
[11]. A. Wilbik, I. Vanderfeesten, D. Bergmans, S. Heines, W. van Mook, Linguistic summaries for compliance analysis of a glucose management clinical protocol, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), (2018) 1-7. https://doi.org/10.1109/FUZZ-IEEE.2018.8491449
[12]. F. E. Boran, D. Akay, A generic method for the evaluation of interval type-2 fuzzy linguistic summaries, IEEE transactions on cybernetics, 44 (2013) 1632-1645. https://doi.org/10.1109/TCYB.2013.2291272
[13]. C. Donis-Diaz, R. Bello, J. Kacprzyk, Linguistic data summarization using an enhanced genetic algorithm, Technical Transactions – Automatic Control, 2013 (2013) 3-12.
[14]. C. Donis-Diaz, A. Muro, R. Bello-Pérez, E. V. Morales, A hybrid model of genetic algorithm with local search to discover linguistic data summaries from creep data, Expert Systems with Applications, 41 (2014) 2035-2042. https://doi.org/10.1016/j.eswa.2013.09.002
[15]. C. H. Nguyen, T. L. Pham, T. N. Nguyen, C. H. Ho, T. A. Nguyen, The linguistic summarization and the interpretability, scalability of fuzzy representations of multilevel semantic structures of word-domains, Microprocessors and Microsystems, 81 (2021) 103641. https://doi.org/10.1016/j.micpro.2020.103641
[16]. C. H. Nguyen, T. S. Tran, D. P. Pham, Modeling of a semantics core of linguistic terms based on an extension of hedge algebra semantics and its application, Knowledge-Based Systems, 67 (2014) 244-262. https://doi.org/10.1016/j.knosys.2014.04.047
[17]. T. L. Pham, C. H. Nguyen, D. P. Pham, Extracting an optimal set of linguistic summaries using genetic algorithm combined with greedy strategy, Journal on Information Technologies & Communications, 2020 (2020) 75-87. https://doi.org/10.32913/mic-ict-research.v2020.n2.954
[18]. D. P. Pham, T. L. Pham, X. T. Tran, A fuzzinness parameter optimization method to extract the optimal set of linguistic summaries from numeric data, TNU Journal of Science and Technology, 229 (2024) 49-57. https://doi.org/10.34238/tnu-jst.9824
[19]. V. T. Hoang, D. D. Nguyen, C. H. Nguyen, A Method to design semantic of linguistics based on the enlarged hedge algebra and applied to building FRBS for solving regression, Journal on Information Technologies & Communications, 38 (2017) 51-57 (In Vietnamese).
[20]. D. D. Nguyen, D. P. Pham, D. V. Pham, D. T. Nguyen, A design method of computational semantics of linguistic words for fuzzy rule-based classifier, Journal on Information Technologies & Communications, 2020 (2020) 9-18 (In Vietnamese). https://doi.org/10.32913/mic-ict-research-vn.v2020.n1.914
[21]. D. D Nguyen, A method for designing fuzzy rule-based classifier using S-function based fuzzy set guarantee interpretability, Transport and Communications Science Journal, 75 (2014) 1335-1347 (In Vietnamese). https://doi.org/10.47869/tcsj.75.3.2
[22]. A. Tarski, A. Mostowski, R. Robinson, Undecidable Theories. North-Holland, 1953.
[23]. J. Kennedy, R. C. Eberhart, Particle Swarm Optimization, Proceedings of the IEEE International Conference on Neural Networks, Piscataway, New Jersey. IEEE Service Center, (1995) 1942-1948.
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24/07/2024
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Kiểu trích dẫn
Pham Dinh, P., & Nguyen Duc, D. (1726333200). A design of computational fuzzy set-based semantics for extracting linguistic summaries. Tạp Chí Khoa Học Giao Thông Vận Tải, 75(7), 2081-2092. https://doi.org/10.47869/tcsj.75.7.6
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