Image analysis – Pattern recognition – Context analysis or word recognition
Reexamination Certificate
2008-01-04
2011-12-13
Chawan, Sheela (Department: 2624)
Image analysis
Pattern recognition
Context analysis or word recognition
C380S240000, C704S001000
Reexamination Certificate
active
08077984
ABSTRACT:
A computer implemented method and an apparatus for comparing spans of text are disclosed. The method includes computing a similarity measure between a first sequence of symbols representing a first text span and a second sequence of symbols representing a second text span as a function of the occurrences of optionally noncontiguous subsequences of symbols shared by the two sequences of symbols. Each of the symbols comprises at least one consecutive word and is defined according to a set of linguistic factors. Pairs of symbols in the first and second sequences that form a shared subsequence of symbols are each matched according to at least one of the factors.
REFERENCES:
patent: 6917936 (2005-07-01), Cancedda
patent: 7058567 (2006-06-01), Ait-Mokhtar et al.
patent: 7836010 (2010-11-01), Hammond et al.
patent: 7933906 (2011-04-01), Hammond et al.
patent: 2005/0137854 (2005-06-01), Cancedda et al.
patent: 2007/0265825 (2007-11-01), Cancedda et al.
U.S. Appl. No. 11/341,788, filed Jan. 27, 2006, Segond, et al.
U.S. Appl. No. 11/378,708, filed Mar. 17, 2006, Roux, et al.
N.Cancedda, E.Gaussier, C.Goutte, J.M.Renders, Word-Sequence Kernels,Journal of Machine Learning Research, 3:1059-1082, 2003.
F.Costa, S.Menchetti, A.Ceroni, A.Passerini, P.Frasconi, Decomposition Kernels For Natural Language Processing, InProc. of the Workshop on Learning Structured Information in Natural Language Applications—EACL, 2006.
C.Giuliano, A.Gliozzo, C.Strapparava, Syntagmatic Kernels: A Word Sense Disambiguation Case Study. InProc. of the Workshop on Learning Structured Information in Natural Language Applications—EACL, 2006.
D.Haussler, Convolution Kernels on Discrete Structures,Technical Report UCSC-CRL-99-10, U.C., Santa Cruz, 1999. URL: http://www.cse.ucsc.edu/haussler/convolutions.ps.
P.Koehn, H.Hoang, Factored Translation Models, inProc. of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 868-876, Prague, 2007.
T.K.Landauer, P.W.Foltz, D.Laham, An Introduction to Latent Semantic Analysis,Discourse Processes, 25:259-284, 1998.
H.Lodhi, C.Saunders, J.Shawe-Taylor, N.Cristianini, C.Watkins, Text Classification Using String Kernels,J. Mach. Learn. Res., 2:419-444, 2002. URL: http://www.ai.mit.edu/proiects/jmIr/papers/volume2/lodhi02a/abstract.html.
K.Papineni, S.Roukos, T.Ward, W.J.Zhu,Bleu: A Method for Automatic Evaluation of Machine Translation, 2001. URL: citeseer.ist.psu.edu/papineni02bleu.html.
Ait-Mokhtar, et al.,Incremental Finite-State Parsing, Proceedings of Applied Natural Language Processing, Washington, Apr. 1997.
S.Ait-Mokhtar, J.P.Chanod, C.Roux, Robustness Beyond Shallowness: Incremental Deep Parsing,Nat. Lang. Eng., 8(3):121-144, 2002. ISSN 1351-3249. doi: http://dx.doi.org/10/1017/S1351324902002887.
J.A.Bilmes, K.Kirchhoff, Factored Language Models and Generalized Parallel Backoff, inNAACL '03: Proc. of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, pp. 4-6, Morristown, NJ, USA, 2003. Association for Computational Linguistics. doi: http://dx.doi.org/10.3115/1073483.1073485.
P.F.Brown, S.A.Della Pietra, V.J.Della Pietra, R.L.Mercer, The Mathematics of Statistical Machine Translation: Parameter Estimation.Computational Linguistics, 19(2):263-311, 1993.
C.Cortes, P.HAFFNERr, M.Mohri, Rational Kernels: Theory and Algorithms,J. Mach. Learn. Res., 5:1035-1062, 2004. ISSN 1533-7928.
G.R.G.Lanckriet, N.Cristianini, M.I.Jordan, W.S.Noble, Kernel-Based Integration of Genomic Data Using Semidefinite Programming, In B. Scholkopl, K. Tsuda, and J.P. Vert, editors,Kernel Methods in Computational Biology, pp. 231-259, MIT Press, 2004.
J.Shawe-Taylor, N.Cristianini,Kernel Methods for Pattern Analysis, Cambridge University Press, 2004.
Ait-Mokhtar, et al.,Subject and Object Dependency Extraction Using Finite-State Transducers, Proceedings ACL'97 Workshop on Information Extraction and the Building of Lexical Semantic Resources for NLP Applications, Madrid, Jul. 1997.
C.Leslie, R.Kuang, Fast String Kernels Using Inexact Matching for Protein Sequences,J. Mach. Learn. Res., 5:1435-1455, 2004.
F.J.Och, D.Gildea, S.Khudanpur, A.Sarkar, K.Yamada, A.Fraser, S.Kumar, L.Shen, D.Smith, K.Eng, V.Jain, Z.Jin, D.Radev, A Smorgasbord of Features for Statistical Machine Translation. InProc. of the 2004 Meeting of the North American Chapter of the Association for Computational Linguistics(NAACL-04), 2004.
F.J.Och, H.Ney, Discriminative Training and Maximum Entropy Models for Statistical Machine Translation, inACL '02: Proc. of the 40th Annual Meeting on Association for Computational Linguistics, pp. 295-302, Morristown, NJ, USA, 2001.
B.Roark, M.Saraclar, M.Collins, M.Johnson, Discriminative Language Modeling With Conditional Random Fields and the Perceptron Algorithm, inACL '04: Proc.of the 42nd Annual Meeting on Association for Computational Linguistics, p. 47, Morristown, NJ, USA, 2004.
L.Shen, A.Sarkar, F.J.Och, Discriminative Reranking For Machine Translation, InProc. of HLTNAACL., 2004.
J.Weston, B.Schlkopf, E.Eskin, C.Leslie, W.S.Noble, Dealing With Large Diagonals in Kernel Matrices.Annals of the Institute of Statistical Mathematics, 55(2):391-408, Jun. 2003 (Abstract).
C.Saunders, H.Tschach, J.Shawe-Taylor, Syllables And Other String Kernel Extensions,In ICML'02: Proc. of the Nineteenth International Conference on Machine Learning, pp. 530-537, San Francisco, CA, USA, 2002. Morgan Kaufmann Publishers Inc. ISBN 1-55860-873-7.
Cancedda Nicola
Mahé Pierre
Chawan Sheela
Xerox Corporation
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