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Volumn , Issue , 2004, Pages 334-341

Learning similarity measures in non-orthogonal space

Author keywords

Latent Semantic Indexing (LSI); Non Orthogonal Space (NOS); Similarity Measures (SM); Vector Space Model (VSM)

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; DATA ACQUISITION; DATA MINING; MATHEMATICAL MODELS; SEMANTICS; VECTORS;

EID: 18744372752     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1031171.1031240     Document Type: Conference Paper
Times cited : (33)

References (15)
  • 1
    • 0033651656 scopus 로고    scopus 로고
    • Latent semantic space: Iterative scaling improves precision of inter-document similarity measurement
    • Athens, Greece
    • Ando, R.K., Latent Semantic Space: Iterative Scaling Improves Precision of Inter-document Similarity Measurement. In Proceedings of the SIGIR, (Athens, Greece, 2000), 216-223.
    • (2000) Proceedings of the SIGIR , pp. 216-223
    • Ando, R.K.1
  • 8
    • 0036161242 scopus 로고    scopus 로고
    • Text categorization with support vector machines. How to represent texts in input space?
    • Leopold, E. and Kinderman, J. Text Categorization with Support Vector Machines. How to Represent Texts in Input Space? Machine Learning, 46. 423-444.
    • Machine Learning , vol.46 , pp. 423-444
    • Leopold, E.1    Kinderman, J.2
  • 10
    • 0347500605 scopus 로고    scopus 로고
    • Heuristics for placing non-orthogonal axial lines to cross the adjacencies between orthogonal rectangles
    • Sanders, I. and Kenny, L., Heuristics for placing non-orthogonal axial lines to cross the adjacencies between orthogonal rectangles. In Proceedings of the 13th Canadian Conference on Computational Geometry, (2001), 153-156.
    • (2001) Proceedings of the 13th Canadian Conference on Computational Geometry , pp. 153-156
    • Sanders, I.1    Kenny, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.