- 1.R. Agrawal, C. Faloutsos, A. Swami, "Efficient Similarity Search in Sequence Databases", Proc. of FODO'93, Lecture Notes in Computer Science 730, Springer Verlag, 69-84. Google ScholarDigital Library
- 2.R. Agrawal, K. Lin, H. S. Sawhney, K. Shim, Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases", Proc. of VLDB'95. Google ScholarDigital Library
- 3.B. Bollobas, G. Das, D. Gunopulos, H. Mannila, Time-Series Similarity Problems and Well-Separated Geometric Sets", Proc. Symposium on Computational Geometry 1997, p. 454-456. Google ScholarDigital Library
- 4.G. Das, D. Gunopulos, H. Mannila, Finding Similar Time Series", Proc. KDD 1997, p. 88-100. Google ScholarDigital Library
- 5.G. Das, K. Lin, H. Mannila, G. Renganathan, P.Smyth, Rule Discovery from Time Series", Proc. KDD 1998, p. 16-22.Google Scholar
- 6.W. Frakes and R. Baeza-Yates, editors. Information Retrieval: Data Structures and Algorithms", Prentice-Hall, 1992. Google ScholarDigital Library
- 7.C. Faloutsos, M. Ranganathan and Y. Manolopoulos, Fast Subsequence Matching in Time-Series Databases",Proc. SIGMOD'94, 419-429. Google ScholarDigital Library
- 8.Y. Wu Huang, P. S. Yu, Adaptive Query Processing for Time-Series Data" Proc. KDD'99, 282-286. Google ScholarDigital Library
- 9.B. Larsen, C. Aone, Fast and effective text mining using linear-time document clustering", Proc. KDD'99, 16 - 22. Google ScholarDigital Library
- 10.D. Rafei, A. Mendelzon, Similarity-Based Queries for Time Series Data", Proc. SIGMOD'97, 13-25. Google ScholarDigital Library
- 11.A. S. Weigend, Data Mining in Finance: Report from the Post-NNCM-96 Workshop on Teaching Computer Intensive Methods for Financial Modeling and Data Analysis (1997)", Proc. Fourth International Conference on Neural Networks in the Capital Markets NNCM-96, p. 399-411.Google Scholar
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- Mining the stock market (extended abstract): which measure is best?
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