메뉴 건너뛰기




Volumn 1, Issue , 2004, Pages 279-284

Linguistic feature extraction using independent component analysis

Author keywords

[No Author keywords available]

Indexed keywords

CODES (SYMBOLS); INDEPENDENT COMPONENT ANALYSIS; INFORMATION RETRIEVAL; MAPS; MATRIX ALGEBRA; NATURAL LANGUAGE PROCESSING SYSTEMS; PRINCIPAL COMPONENT ANALYSIS; SEMANTICS; SYNTACTICS; VECTORS;

EID: 10944239536     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (13)

References (22)
  • 2
    • 84936824188 scopus 로고
    • Word association norms, mutual information and lexicography
    • K.W. Church and P. Hanks. Word association norms, mutual information and lexicography. Computational Linguistics, 16:22-29, 1990.
    • (1990) Computational Linguistics , vol.16 , pp. 22-29
    • Church, K.W.1    Hanks, P.2
  • 3
    • 0028416938 scopus 로고
    • Independent component analysis - A new concept?
    • P. Comon. Independent component analysis - a new concept? Signal Processing, 36:287-314, 1994.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Comon, P.1
  • 5
    • 1842397531 scopus 로고
    • chapter The case for case, Holt, Rinehart and Winston, Inc.
    • Ch.J. Fillmore. Universals in Linguistic Theory, chapter The case for case, pages 1-88. Holt, Rinehart and Winston, Inc., 1968.
    • (1968) Universals in Linguistic Theory , pp. 1-88
    • Fillmore, Ch.J.1
  • 6
    • 0345331809 scopus 로고
    • Unsupervised methods for finding linguistic categories
    • I. Aleksander and J. Taylor, editors, North-Holland
    • S. Finch and N. Chater. Unsupervised methods for finding linguistic categories. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks, 2, pages 11-1365-1368. North-Holland, 1992.
    • (1992) Artificial Neural Networks , vol.2
    • Finch, S.1    Chater, N.2
  • 8
    • 0242557035 scopus 로고    scopus 로고
    • Learning to understand - General aspects of using self-organizing maps in natural language processing
    • American Institute of Physics, Woodbury, New York
    • T. Honkela. Learning to Understand - General Aspects of Using Self-Organizing Maps in Natural Language Processing In Computing Anticipatory Systems, pages 563-576. American Institute of Physics, Woodbury, New York, 1997.
    • (1997) Computing Anticipatory Systems , pp. 563-576
    • Honkela, T.1
  • 10
    • 0032629347 scopus 로고    scopus 로고
    • Fast and robust fixed-point algorithms for independent component analysis
    • A. Hyvärinen. Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks, 10:626-634, 1999.
    • (1999) IEEE Transactions on Neural Networks , vol.10 , pp. 626-634
    • Hyvärinen, A.1
  • 12
    • 84898995610 scopus 로고    scopus 로고
    • Restructuring sparse high dimensional data for effective retrieval
    • C. Isbell and P. Viola. Restructuring sparse high dimensional data for effective retrieval. In Advances in Neural Information Processing Systems, volume 11, pages 480-486, 1998.
    • (1998) Advances in Neural Information Processing Systems , vol.11 , pp. 480-486
    • Isbell, C.1    Viola, P.2
  • 13
    • 0026191274 scopus 로고
    • Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture
    • C. Jutten and J. Hérault. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture. Signal Processing, 24:1-10, 1991.
    • (1991) Signal Processing , vol.24 , pp. 1-10
    • Jutten, C.1    Hérault, J.2
  • 15
    • 0000600219 scopus 로고    scopus 로고
    • A solution to plato's problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge
    • T. Landauer and S. Dumais. A solution to plato's problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104:211-240, 1997.
    • (1997) Psychological Review , vol.104 , pp. 211-240
    • Landauer, T.1    Dumais, S.2
  • 19
    • 0031238559 scopus 로고    scopus 로고
    • Self-organizing feature map model of the lexicon
    • R. Miikkulainen. Self-organizing feature map model of the lexicon. Brain and Language, 59:334-366, 1997.
    • (1997) Brain and Language , vol.59 , pp. 334-366
    • Miikkulainen, R.1
  • 20
    • 34249971816 scopus 로고
    • Self-organizing semantic maps
    • H. Ritter and T. Kohonen. Self-organizing semantic maps. Biological Cybernetics, 61(4):241-254, 1989.
    • (1989) Biological Cybernetics , vol.61 , Issue.4 , pp. 241-254
    • Ritter, H.1    Kohonen, T.2
  • 21
    • 0016572913 scopus 로고
    • A vector space model for automatic indexing
    • G. Salton, A. Wong, and C. S. Yang. A vector space model for automatic indexing. Communications of the ACM, 18(11):613-620, 1975.
    • (1975) Communications of the ACM , vol.18 , Issue.11 , pp. 613-620
    • Salton, G.1    Wong, A.2    Yang, C.S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.