Uncovering the hierarchical structure of text archives by using an unsupervised neural network with adaptive architecture

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

Volumn 1805, Issue , 2000, Pages 384-395

  Merkl, Dieter ^a   Rauber, Andreas ^a  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

CONFORMAL MAPPING; SELF ORGANIZING MAPS; TREES (MATHEMATICS);

ADAPTIVE ARCHITECTURE; DATA MINING APPLICATIONS; GROWING HIERARCHICAL SELF-ORGANIZING MAPS; HIERARCHICAL STRUCTURES; HIGH-DIMENSIONAL FEATURE SPACE; INFORMATION RETRIEVAL DOMAIN; NEURAL NETWORK MODEL; UNSUPERVISED NEURAL NETWORKS;

DATA MINING;

EID: 2042525150     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45571-x_46     Document Type: Conference Paper

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