Temporal Linguistic Summaries of Time Series Using Fuzzy Logic

Communications in Computer and Information Science

Volumn 80 PART 1, Issue , 2010, Pages 436-445

  Kacprzyk, Janusz ^a   Wilbik, Anna ^a  

^a SYSTEMS RESEARCH INSTITUTE   (Poland)

Author keywords

[No Author keywords available]

Indexed keywords

COGNITIVE SCIENCE; HUMAN DECISION MAKING; INVESTMENT DECISIONS; INVESTMENT FUNDS; LINGUISTIC SUMMARIES; PROTOFORMS; SHORT SEGMENTS;

DATA PROCESSING; FUZZY LOGIC; INVESTMENTS; KNOWLEDGE BASED SYSTEMS; LINGUISTICS; TIME SERIES;

INFORMATION MANAGEMENT;

EID: 80053074097     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-14055-6_45     Document Type: Conference Paper

References (24)

1. Kacprzyk, J., Wilbik, A., Zadrozny, S.: Linguistic summarization of trends: a fuzzy logic based approach. In: Proceedings of the 11th International Conference Information Processing and Management of Uncertainty in Knowledge-based Systems, pp. 2166-2172 (2006)
2. Kacprzyk, J., Wilbik, A., Zadrozny, S.: On some types of linguistic summaries of time series. In: Proceedings of the 3rd International IEEE Conference Intelligent Systems, pp. 373-378. IEEE Press, Los Alamitos (2006)
3. Kacprzyk, J., Wilbik, A., Zadrozny, S.: Linguistic summarization of time series using a fuzzy quantifier driven aggregation. Fuzzy Sets and Systems 159(12), 1485-1499 (2008)
4. Kacprzyk, J., Wilbik, A.: An extended, specificity based approach to linguistic summarization of time series. In: Proceedings of the 12th International Conference Information Processing and Management of Uncertainty in Knowledge-based Systems, pp. 551-559 (2008)
5. Kacprzyk, J., Wilbik, A.: A new insight into the linguistic summarization of time series via a degree of support: Elimination of infrequent patterns. In: Dubois, et al. (eds.) Soft Methods for Handling Variability and Imprecision, pp. 393-400. Springer, Heidelberg (2008)
6. Kacprzyk, J., Wilbik, A.: Linguistic summarization of time series using linguistic quantifiers: augmenting the analysis by a degree of fuzziness. In: Proceedings of 2008 IEEE World Congress on Computational Intelligence, pp. 1146-1153. IEEE Press, Los Alamitos (2008)
7. Past performance does not predict future performance, http://www.freemoneyfinance.com/2007/01/past_performanc.html
8. Past performance is not everything, www.personalfn.com/detail.asp?date=9/1/2007
9. New year's eve:past performance is no indication of future return stockcasting, blogspot.com/2005/12/new-years-evepast-performance-is-no.html
10. Myers, R.: Using past performance to pick mutual funds. Nation's Business (1997), findarticles.com/p/articles/mi_m1154/is_n10_v85/ai_19856416
11. Bogle, J.C.: Common Sense on Mutual Funds: New Imperatives for the Intelligent Investor. Wiley, New York (1999)
12. U.S. Securities and Exchange Commission: Mutual fund investing: Look at more than a fund's past performance, www.sec.gov/investor/pubs/mfperform.htm
13. Ariely, D., Zakay, D.: A timely account of the role of duration in decision making. Acta Psychologica 108(2), 187-207 (2001)
14. Rachlin, H.: Judgment, Decision, and Choice: A Cognitive/Behavioral Synthesis. W.H. Freeman & Company, New York (1989)
15. Liberman, N., Trope, Y.: The role of feasibility and desirability considerations in near and distant future decisions: A test of temporal construal theory. Journal of Personality and Social Psychology 75, 5-18 (1998)
16. Yager, R.R.: A new approach to the summarization of data. Information Sciences 28, 69-86 (1982)
17. Zadeh, L.A.: Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets and Systems 9(2), 111-127 (1983)
18. Keogh, E., Chu, S., Hart, D., Pazzani, M.: An online algorithm for segmenting time series. In: Proceedings of the 2001 IEEE International Conference on Data Mining (2001)
19. Keogh, E., Chu, S., Hart, D., Pazzani, M.: Segmenting time series: A survey and novel approach. In: Last, M., Kandel, A., Bunke, H. (eds.) Data Mining in Time Series Databases. World Scientific Publishing, Singapore (2004)
20. Batyrshin, I.: On granular derivatives and the solution of a granular initial value problem. International Journal Applied Mathematics and Computer Science 12(3), 403-410 (2002)
21. Batyrshin, I., Sheremetov, L.: Perception based functions in qualitative forecasting. In: Batyrshin, et al. (eds.) Perception-based Data Mining and Decision Making in Economics and Finance. Springer, Heidelberg (2006)
22. Zadeh, L.A.: A prototype-centered approach to adding deduction capabilities to search engines - the concept of a protoform. In: Proceedings of the Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2002), pp. 523-525 (2002)
23. Kacprzyk, J., Zadrozny, S.: Linguistic database summaries and their protoforms: toward natural language based knowledge discovery tools. Information Sciences 173, 281-304 (2005)
24. Kacprzyk, J., Wilbik, A., Zadrozny, S.: Linguistic summarization of time series under different granulation of describing features. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 230-240. Springer, Heidelberg (2007)