Morphological analysis by multiple sequence alignment

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6241 LNCS, Issue , 2010, Pages 666-673

  Tchoukalov, Tzvetan ^a   Monson, Christian ^b   Roark, Brian ^b  

^a STANFORD UNIVERSITY   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL SEQUENCES; CONTEXT-FREE; FUTURE RESEARCH DIRECTIONS; HUNGARIANS; INDUCTION SYSTEM; LONG-DISTANCE DEPENDENCIES; MORPHOLOGICAL ANALYSIS; MULTIPLE SEQUENCE ALIGNMENTS; NATURAL LANGUAGES; POLYNOMIAL COMPLEXITY; RELATED WORD; STATE-OF-THE-ART PERFORMANCE; TEXT CORPORA; THREE-DIMENSIONAL STRUCTURE OF PROTEIN; UNIQUE WORD;

ALIGNMENT; INFORMATION RETRIEVAL; LINGUISTICS; SOFTWARE AGENTS; THREE DIMENSIONAL;

MORPHOLOGY;

EID: 78049349818     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15754-7_80     Document Type: Conference Paper

References (10)

1. Durbin, R., Eddy, S. R., Krogh, A., Mitchison, G.: Biological Sequence Analysis: Probabilis-tic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge (1998)
2. Baroni, M., Matiasek, J., Trost, H.: Unsupervised Discovery of Morphologically Related Words Based on Orthographic and Semantic Similarity. In: ACL Special Interest Group in Computational Phonology in Cooperation with the ACL Special Interest Group in Natural Language Learning (SIGPHON/SIGNLL), Philadelphia, Pennsylvania, pp. 48-57 (2002)
3. Wicentowski, R.: Modelling and Learning Multilingual Inflectional Morphology in a Minimally Supervised Framework. Ph. D. Thesis, The Johns Hopkins University, Baltimore, Maryland (2002)
4. Feng, D. F., Doolittle, R. F.: Progressive Sequence Alignment as a Prerequisite to Correct Phylogenetic Trees. Journal of Molecular Evolution 25(4), 351-360 (1987)
5. Gotoh, O.: Significant Improvement in Accuracy of Multiple Protein Sequence Alignments by Iterative Refinement as Assessed by Reference to Structural Alignments. Journal of Molecular Biology 264(4), 823-838 (1996)
6. Monson, C., Hollingshead, K., Roark, B.: Simulating Morphological Analyzers with Stochastic Taggers for Confidence Estimation. In: 10th Workshop of the Cross-Language Eval-uation Forum, CLEF 2009, Corfu, Greece, Revised Selected Papers. LNCS, Springer, Heidelberg (2010)
7. Kurimo, M., Virpioja, S., Turunen, V. T., Blackwood, G. W., Byrne, W.: Overview and Results of Morpho Challenge 2009. In: 10th Workshop of the Cross-Language Evaluation Forum, CLEF 2009, Corfu, Greece, Revised Selected Papers. LNCS, Springer, Heidelberg (2010)
8. Creutz, M.: Induction of the Morphology of Natural Language: Unsupervised Morpheme Segmentation with Application to Automatic Speech Recognition. Ph. D. Thesis, Computer and Information Science, Report D13, Helsinki, University of Technology, Espoo, Finland (2006)
9. Trón, V., Gyepesi, G., Halácsy, P., Kornai, A., Németh, L., Varga, D.: Hunmorph: Open Source Word Analysis. In: ACL Workshop on Software (2005)
10. Varga, D., Halácsy, P., Kornai, A., Németh, L., Trón, V., Váradi, T., Sass, B., Bottyán, G., Héja, E., Gyarmati, Á., Mészáros, Á., Labundy, D.: Hunglish Corpus (2009), http://mokk.bme.hu/resources/hunglishcorpus (accessed on August 18, 2009)