Computing with words, protoforms and linguistic data summaries : towards a novel natural language based data mining and knowledge discovery tools

• Autorzy: Kacprzyk J. , Zadrożny S.

Identyfikatory

DOI

10.14313/JAMRIS_4-2013/27

• Języki publikacji: EN

Abstrakty

EN

We show how Zadeh’s idea of computing with words and perceptions, based on his concept of a precisiated natural language (PNL), can lead to a new direction in the use of natural language in data mining, linguistic data(base) summaries. We emphasize the relevance of Zadeh’s another idea, that of a protoform, and show that various types of Yager type linguistic data summaries may be viewed as items in a hierarchy of protoforms of summaries. We briefly present an implementation for a sales database of a computer retailer as a convincing example that these tools and techniques are implementable and functional. These summaries involve both data from an internal database of the company and data downloaded from external databases via the Internet.

Słowa kluczowe

EN

computing with words; linguistic summaries; protoform

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2014
• Tom: Vol. 8, No. 3
• Strony: 52--58
• Opis fizyczny: Bibliogr. 50 poz., rys.

Twórcy

autor

Kacprzyk J.

• Systems Research Institute Polish Academy of Sciences, ul.Newelska 6, 01–447 Warszawa, Poland,

autor

Zadrożny S.

• Systems Research Institute Polish Academy of Sciences, ul.Newelska 6, 01–447 Warszawa, Poland,

Bibliografia

• [1] Agrawal R., Srikant R., ”Fast algorithms for mining association rules”. In: Proceedings of the 20thInternational Conference on Very Large Databases, Santiago de Chile, 1994.
• [2] Au W.-H., Chan K.C.C., ”FARM: A data mining system for discovering fuzzy association rules”. In: Proceedings of the 8th IEEE International Conference on Fuzzy Systems, Seoul, Korea, 1999, 1217–1222.
• [3] Berzal F., Cubero J.C., Marı́n N., Vila M.A., Kacprzyk J. and Zadrożny S. , ”A General framework for computing with words in objectoriented programming”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 15, 2007, 111–131. DOI: http://dx.doi.org/10.1142/S0218488507004480.
• [4] Bosc P. , Dubois D., Pivert O. , Prade H., de Calmes M., ”Fuzzy summarization of data using fuzzy cardinalities”. In: Proceedings of IPMU 2002, , Annecy, France, 2002, 1553–1559.
• [5] Chen G., Wei Q., Kerre E., ”Fuzzy data mining: discovery of fuzzy generalized association rules”. In: G. Bordogna and G. Pasi (Eds.): Recent Issues on Fuzzy Databases. Springer-Verlag, Heidelberg and New York, 2000, 45–66. DOI: http://dx.doi.org/10.1007/978-3-7908-1845-1.
• [6] Dubois D., Fargier H., Prade H., ”Beyond min aggregation in multicriteria decision: (ordered) weighted min, discri-min,leximin”. In: R.R. Yager and J. Kacprzyk (Eds.): The Ordered Weighted Averaging Operators. Theory and Applications, Kluwer, Boston, 1997, 181–192.
• [7] Dubois D., Prade H., ”Gradual rules in approximate reasoning”, Information Sciences, vol. 61, 1992, 103–122.
• [8] Dubois D., Prade H., ”Fuzzy sets in approximate reasoning, Part 1: Inference with possibility distributions”, Fuzzy Sets and Systems, vol. 40, 1991, 143–202. DOI: http://dx.doi.org/10.1016/0165-0114(91)90050-Z.
• [9] Bosc P., Dubois D., Prade H., ”Fuzzy functional dependencies – an overview and a critical discussion”. In: Proceedings of 3rd IEEE International Conference on Fuzzy Systems, Orlando, USA, 1994, 325–330. DOI: http://dx.doi.org/10.1109/FUZZY.1994.343753.
• [10] George R. , Srikanth R., ”Data summarization using genetic algorithms and fuzzy logic”. In: F. Herrera, J.L. Verdegay (Eds.): Genetic Algorithms and Soft Computing, Springer-Verlag, Heidelberg, 1996, 599–611.
• [11] George R. , Srikanth R., ”A soft computing approach to intensional answering in databases”, Journal of Automation, Mobile Robotics & Intelligent Systems VOLUME 8, N◦ 3 2014 Information Sciences, vol. 92, no. 1–4, 1996, 313–328. DOI: http://dx.doi.org/10.1016/0020-0255(96)00049-7.
• [12] Glöckner I., ”Fuzzy quantifiers, multiple variable binding, and branching quantification”. In:T.Bilgi c et al.: IFSA 2003. LNAI 2715, Springer-Verlag, Berlin and Heidelberg, 2003, 135–142.
• [13] Hájek P., Holeňa M., ”Formal logics of discovery and hypothesis formation by machine”, Theoretical Computer Science, vol. 292, 2003,345–357. DOI: http://dx.doi.org/10.1007/3-540-49292-5_26.
• [14] Hu Y.-Ch., Chen R.-Sh., Tzeng G.-H, ”Mining fuzzy association rules for classification problems”,Computers and Industrial Engineering, vol. 43, no. 4, 2002, 735–750. DOI: http://dx.doi.org/10.1016/S0360-8352(02)00136-5.
• [15] Kacprzyk J., Strykowski P., ”Linguistic data summaries for intelligent decision support”. In: R. Felix (Ed.): Fuzzy Decision Analysis and Recognition Technology for Management, Planning and Optimization - Proceedings of EFDAN’99, Dortmund, Germany, 1999, 3–12.
• [16] Kacprzyk J., Strykowski P., ”Linguitic summaries of sales data at a computer retailer: a case study”.In: Proceedings of IFSA’99, vol. 1, 1999, Taipei, Taiwan R.O.C, 29–33.
• [17] Kacprzyk J., Wilbik A., Zadrożny S., ”Linguistic summarization of time series using a fuzzy quantifier driven aggregation”, Fuzzy Sets and Systems,vol. 159, no. 12, 2008, 1485–1499. DOI: http://dx.doi.org/10.1016/j.fss.2008.01.025.
• [18] Kacprzyk J., Wilbik A., Zadrożny S., ”An approach to the linguistic summarization of time series using a fuzzy quantifier driven aggregation”, International Journal of Intelligent Systems, vol. 25, no. 5, 2010, 411–439. DOI: http://dx.doi.org/10.1002/int.20405.
• [19] Kacprzyk J., Yager R.R., ”Linguistic summaries of data using fuzzy logic”, International Journal of General Systems, vol. 30, no. 2, 2001,33–154. DOI: http://dx.doi.org/10.1080/03081070108960702.
• [20] Kacprzyk J., Yager R.R., Zadrożny S., ”A fuzzy logic based approach to linguistic summaries of databases”, International Journal of Applied Mathematics and Computer Science, 10, 2000, 813–834.
• [21] Kacprzyk J., Yager R.R., Zadrożny S., ”Fuzzy linguistic summaries of databases for an efficient business data analysis and decision support. In W. Abramowicz and J. Zurada (Eds.): Knowledge Discovery for Business Information Systems, pp. 129-152, Kluwer, Boston, 2001.
• [22] Kacprzyk J., Yager R.R., Zadrożny S., ”FQUERY for Access: fuzzy querying for a Windowsbased DBMS”. In: P. Bosc and J. Kacprzyk (Eds.): Fuzziness in Database Management Systems, Springer-Verlag, Heidelberg, 1995, 415-433. DOI: http://dx.doi.org/10.1007/978-3-7908-1897-0_18.
• [23] Kacprzyk J., Zadrożny S., ”Protoforms of linguistic data summaries: towards more general natural-language-based data mining tools”. In: A. Abraham, J. Ruiz-del-Solar, M. Koeppen (Eds.): Soft Computing Systems, pp. 417 - 425, IOS Press, Amsterdam, 2002.
• [24] Kacprzyk J., Zadrożny S., ”Data Mining via Linguistic Summaries of Data: An Interactive Approach”. In: T. Yamakawa and G. Matsumoto (Eds.): Methodologies for the Conception, Design and Application of Soft Computing. Proc. of IIZUKA’98, Iizuka, Japan, 1998, 667–668.
• [25] Kacprzyk J., Zadrożny S., ”The paradigm of computing with words in intelligent database querying”. In: L.A. Zadeh and J. Kacprzyk (Eds.): Computing with Words in Information/Intelligent Systems. Part 2. Foundations, Springer–Verlag, Heidelberg and New York, 1999, 382–398. DOI: http://dx.doi.org/10.1007/978-3-7908-1872-7.
• [26] Kacprzyk J., Zadrożny S., ”Computing with words: towards a new generation of linguistic querying and summarization of databases”. In: P. Sinčak and J. Vaščak (Eds.): Quo Vadis Computational Intelligence?, Springer-Verlag, Heidelberg and New York, 2000, 144–175, .
• [27] Kacprzyk J., Zadrożny S., ”On a fuzzy querying and data mining interface”, Kybernetika, vol. 36, 2000, 657–670.
• [28] Kacprzyk J., Zadrożny S., ”On combining intelligent querying and data mining using fuzzy logic concepts”. In: G. Bordogna and G. Pasi (Eds.): Recent Research Issues on the Management of Fuzziness in Databases, Springer–Verlag, Heidelberg and New York, 2000, 67–81.
• [29] Kacprzyk J., Zadrożny S., ”Data mining via linguistic summaries of databases: an interactive approach”. In: L. Ding (Ed.): A New Paradigm of Knowledge Engineering by Soft Computing, World Scientific, Singapore, 2001, 325–345. DOI: http: //dx.doi.org/10.1142/4606.
• [30] Kacprzyk J., Zadrożny S., ”Computing with words in intelligent database querying: standalone and Internet-based applications”, Information Sciences, vol. 134, no. 1–4, 2001, 71–109. DOI: http://dx.doi.org/10.1016/S0020-0255(01)00093-7.
• [31] Kacprzyk J., Zadrożny S., ”On linguistic approaches in flexible querying and mining of association rules”’. In: H.L. Larsen, J. Kacprzyk, S. Zadrożny, T. Andreasen and H. Christiansen (Eds.): Flexible Query Answering Systems. Recent Advances, Springer-Verlag, Heidelberg and New York, 2001, 475–484.
• [32] Kacprzyk J., Zadrożny S., ”Linguistic summarization of data sets using association rules”. In: Proceedings of The IEEE International Conference on Fuzzy Systems, St. Louis, USA, 2003, 702–707.
• [33] Kacprzyk J., Zadrożny S., ”Computing with words is an implementable paradigm: fuzzy queries, linguistic data summaries, and natural language generation”, IEEE Transactions on Fuzzy Systems, vol. 18, no. 3, 2010, 461–472. DOI: http://dx.doi.org/10.1109/TFUZZ.2010.2040480.
• [34] Kacprzyk J., Zadrożny S., ”Computing with words and protoforms: powerful and far reaching ideas”. In: Rudolf Seising, Enric Trillas, Claudio Moraga, and Settimo Termini (Eds.): On Fuzziness. Springer-Verlag, Berlin Heidelberg 2013,255–270. DOI: http://dx.doi.org/10.1007/978-3-642-35641-4.
• [35] Kacprzyk J., Zadrożny S., ”Comprehensiveness of Linguistic Data Summaries: A Crucial Role of Protoforms”. In: Ch. Moewes and A. Nürnberger (Eds.): Computational Intelligence in Intelligent Data Analysis. Springer-Verlag, Berli, Heidelberg 2013, 207–221. DOI: http://dx.doi.org/10.1007/978-3-642-32378-2.
• [36] Kacprzyk J., Zadrożny S., ”Derivation of Linguistic Summaries is Inherently Difficult: Can Association Rule Mining Help?” In: Borgelt Ch., Gil M. A., Sousa J. M. C., Verleysen M. (Eds.): Towards Advanced Data Analysis by Combining Soft Computing and Statistics, Springer-Verlag, 2013,291–303. DOI: http://dx.doi.org/10.1007/978-3-642-30278-7.
• [37] Lee J.-H., Lee-Kwang H., ”An extension of association rules using fuzzy sets”. In: Proceedings of the Seventh IFSA World Congress, Prague, Czech Republic, 1997, 399–402.
• [38] Liu Y., Kerre E.E., ”An overview of fuzzy quantifiers. (I). Interpretations”, Fuzzy Sets and Systems, vol. 95, 1998, 1–21.
• [39] Mannila H., Toivonen H., Verkamo A.I., ”Efficient algorithms for discovering association rules”. In: U.M. Fayyad and R. Uthurusamy (Eds.): Proceedings of the AAAI Workshop on Knowledge Discovery in Databases, Seattle, USA, 1994, 181–192.
• [40] Raschia G., Mouaddib N., ”SAINTETIQ: a fuzzy set-based approach to database summarization”, Fuzzy Sets and Systems, vol. 129, no. 2, 2002, pp. 137–162. DOI: http://dx.doi.org/10.1016/S0165-0114(01)00197-X.
• [41] Rasmussen D., Yager R.R, ”Fuzzy query language for hypothesis evaluation”. In: Andreasen T., H.Christiansen and H. L. Larsen (Eds.): Flexible Query Answering Systems, pp. 23 - 43, Kluwer, Boston, 1997. DOI: http://dx.doi.org/10.1007/978-1-4615-6075-3_2.
• [42] Rasmussen D., Yager R.R, ”Finding fuzzy and gradual functional dependencies with SummarySQL”, Fuzzy Sets and Systems, vol. 106, no. 2, 1999, 131–142. DOI: http://dx.doi.org/10.1016/S0165-0114(97)00268-6.
• [43] Yager R.R, ”A new approach to the summarization of data”, Information Sciences, vol. 28, no. 1, 1982, 69–86. DOI: http://dx.doi.org/10.1016/0020-0255(82)90033-0.
• [44] Yager R.R, ”On linguistic summaries of data”. In: W. Frawley and G. Piatetsky-Shapiro (Eds.): Knowledge Discovery in Databases. AAAI/MIT Press, 1991, 347–363.
• [45] Yager R.R, Kacprzyk J. (Eds.), The Ordered Weighted Averaging Operators: Theory and Applications, Kluwer, Boston, 1997.
• [46] Zadeh L.A., ”A computational approach to fuzzy quantifiers in natural languages”, Computers and Mathematics with Applications, vol. 9, no. 1, 1983, 149–184. DOI: http://dx.doi.org/10.1016/0898-1221(83)90013-5.
• [47] Zadeh L.A., A prototype-centered approach to adding deduction capabilities to search engines -– the concept of a protoform, BISC Seminar, 2002, University of California, Berkeley, 2002. DOI: http://dx.doi.org/10.1109/IS. 2002.1044219.
• [48] Zadeh L.A., Kacprzyk J. (Eds.), Computing with Words in Information/Intelligent Systems. Part 1. Foundations. Part 2. Applications, Springer – Verlag, Heidelberg and New York, 1999. DOI: http://dx.doi.org/10.1007/978-3-7908-1873-4 (part 1) and DOI: http://dx.doi.org/10.1007/978-3-7908-1872-7.
• [49] Zadrożny S., Kacprzyk J., ”Computing with words for text processing: an approach to the text categorization”, Information Sciences, vol. 176, no. 4, 006, 415–437. DOI: http://dx.doi.org/10.1016/j.ins.2005.07.017.
• [50] Zadrożny S., Kacprzyk J., ”Issues in the practical use of the OWA operators in fuzzy querying”, Journal of Intelligent Information Systems, vol. 33, no. 3, 2009, 307–325. DOI: http://dx.doi.org/10.1007/s10844-008-0068-1.