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Latent Dirichlet Allocation

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JournalofMachineLearningResearch3 CA94720,USAAndrewY. UniversityStanford, CA94305,USAMichaelI. CA94720,USAEditor:JohnLaffertyAbstractWe describelatentDirichletallocation(LDA),a generative is a three-level hierarchicalBayesianmodel,inwhicheachite mofa collectionis modeledasa finitemixtureover ,inturn, ,thetopicprobabilitiesprovideanexplicitr epresentationofa reportresultsindocumentmodeling,textclas sification,andcollaborative filtering,comparingtoa collectionthatenableefficientprocessingo flargecollectionswhilepreservingtheessen tialstatisticalrelationshipsthatareusefu lforbasictaskssuchasclassification,novel tydetection,summarization, (IR)(Baeza-YatesandRibeiro-Neto,1999).

The LDA model is presented in Section 3 and is compared to related latent variable models in Section 4. We discuss inference and parameter estimation for LDA in Section 5. An illustrative example of fitting LDA to data is provided in Section 6. Empirical results in text modeling, text

  Model, Talent, Variable, Latent variable models

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