Efficient Discovery of Proximity Patterns with Suffix Arrays (Extended Abstract)

作者: Hiroki Arimura , Hiroki Asaka , Hiroshi Sakamoto , Setsuo Arikawa

DOI: 10.1007/3-540-48194-X_14

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摘要: We describe an efficient implementation of a text mining algorithm for discovering class simple string patterns. With index structure, called the virtual suffix tree, pattern discovery built on top array, resulting is and fast in practice compared with previous tree.

参考文章(16)
Toru Kasai, Gunho Lee, Hiroki Arimura, Setsuo Arikawa, Kunsoo Park, Linear-Time Longest-Common-Prefix Computation in Suffix Arrays and Its Applications combinatorial pattern matching. pp. 181- 192 ,(2001) , 10.1007/3-540-48194-X_17
Shinichi Morishita, On Classification and Regression discovery science. pp. 40- 57 ,(1998) , 10.1007/3-540-49292-5_4
Ricardo A. Baeza-Yates, Gaston H. Gonnet, Tim Snider, New indices for text: PAT Trees and PAT arrays Information Retrieval. pp. 66- 82 ,(1992)
Hiroki Arimura, Atsushi Wataki, Ryoichi Fujino, Setsuo Arikawa, A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases algorithmic learning theory. pp. 247- 261 ,(1998) , 10.1007/3-540-49730-7_19
Shinichi Shimozono, Hiroki Arimura, Setsuo Arikawa, Efficient discovery of optimal word-association patterns in large text databases New Generation Computing. ,vol. 18, pp. 49- 60 ,(2000) , 10.1007/BF03037568
Michael J. Kearns, Robert E. Schapire, Linda M. Sellie, Toward efficient agnostic learning conference on learning theory. ,vol. 17, pp. 341- 352 ,(1992) , 10.1145/130385.130424