A heuristic approach to determine an appropriate number of topics in topic modeling

BMC Bioinformatics

Volumn 16, Issue 13, 2015, Pages

  Zhao, Weizhong ^a,b   Chen, James J ^a   Perkins, Roger ^a   Liu, Zhichao ^a   Ge, Weigong ^a   Ding, Yijun ^a   Zou, Wen ^a  

^a NATIONAL CENTER FOR TOXICOLOGICAL RESEARCH   (United States)

^b XIANGTAN UNIVERSITY   (China)

Author keywords

Latent Dirichlet allocation (LDA); Perplexity; Rate of perplexity change (RPC); Topic number

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; DATA MINING; ITERATIVE METHODS; LEARNING SYSTEMS; NUMERICAL METHODS; STATISTICS;

ANALYSIS OF VARIATIONS; COMPUTATIONAL BIOLOGY; LATENT DIRICHLET ALLOCATIONS; NEXT-GENERATION SEQUENCING; NUMERICAL EXPERIMENTS; PERPLEXITY; SUBJECTIVE EVALUATIONS; TOPIC NUMBER;

HEURISTIC METHODS;

BIOLOGY; DATA MINING; FACTUAL DATABASE; HEURISTICS; HIGH THROUGHPUT SEQUENCING; PHYSIOLOGY; PROCEDURES;

COMPUTATIONAL BIOLOGY; DATA MINING; DATABASES, FACTUAL; HEURISTICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING;

EID: 84961612892     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-16-S13-S8     Document Type: Article

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