A mixed similarity measure in near-linear computational complexity for distance-based methods

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

Volumn 1910, Issue , 2000, Pages 211-220

  Nguyen, Ngoc Binh ^a,b   Ho, Tu Bao ^a  

^a JAPAN ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

^b HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Viet Nam)

Author keywords

Computational complexity; Distance based methods; Mixed similarity measure (MSM); Very large databases

Indexed keywords

COMPUTATIONAL COMPLEXITY; LARGE DATASET; METADATA;

DATA MINING METHODS; DISTANCE-BASED METHODS; HETEROGENEOUS DATASETS; KNOWLEDGE DISCOVERY AND DATA MININGS; NEAREST NEIGHBOR CLASSIFICATION; SIMILARITY MEASURE; TIME AND SPACE COMPLEXITY; VERY LARGE DATABASE;

DATA MINING;

EID: 84974725344     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45372-5_21     Document Type: Conference Paper

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