Latent Dirichlet Allocation (LDA)
GPTKB entity
Statements (52)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:topic_model
gptkb:statistical_analysis |
| gptkbp:application |
recommender systems
customer feedback analysis social media analysis scientific literature analysis news article analysis |
| gptkbp:assumes |
bag-of-words model
exchangeability of documents exchangeability of words |
| gptkbp:basedOn |
gptkb:Dirichlet_distribution
|
| gptkbp:citation |
highly cited
|
| gptkbp:developedBy |
gptkb:Andrew_Ng
gptkb:David_Blei gptkb:Michael_I._Jordan |
| gptkbp:extendsTo |
correlated topic model
dynamic topic model hierarchical LDA online LDA supervised LDA |
| gptkbp:field |
gptkb:artificial_intelligence
gptkb:machine_learning information retrieval statistics text mining |
| gptkbp:generalizes |
mixture of unigrams model
|
| gptkbp:inferenceMethod |
gptkb:Gibbs_sampling
variational Bayes |
| gptkbp:input |
corpus of documents
|
| gptkbp:introducedIn |
2003
|
| gptkbp:openSource |
gptkb:Gensim
gptkb:MALLET gptkb:scikit-learn Stanford Topic Modeling Toolbox |
| gptkbp:output |
topics
topic distributions word distributions |
| gptkbp:parameter |
number of topics
Dirichlet prior alpha Dirichlet prior beta |
| gptkbp:publishedIn |
gptkb:Journal_of_Machine_Learning_Research
|
| gptkbp:relatedTo |
gptkb:machine_learning
gptkb:probabilistic_latent_semantic_analysis natural language processing non-negative matrix factorization |
| gptkbp:supportsAlgorithm |
unsupervised learning
|
| gptkbp:usedFor |
information retrieval
topic modeling document classification |
| gptkbp:bfsParent |
gptkb:symmetric_Dirichlet_distribution
|
| gptkbp:bfsLayer |
8
|
| https://www.w3.org/2000/01/rdf-schema#label |
Latent Dirichlet Allocation (LDA)
|