Keywords
Probabilistic latent semantic analysisComputer sciencePerplexityArtificial intelligenceProbabilistic logicLatent variable modelInferenceLatent variableLatent class modelSemantics (computer science)Natural language processingMachine learningLanguage model
Affiliated Institutions
Related Publications
Probabilistic Latent Semantic Indexing
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. F...
Probabilistic graphical models : principles and techniques
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented i...
From Machine Learning to Machine Reasoning
A plausible definition of "reasoning" could be "algebraically manipulating previously acquired knowledge in order to answer a new question". This definition covers first-order l...
A comparison of event models for naive bayes text classification
Recent work in text classification has used two different first-order probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multi-va...
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning un...
Publication Info
- Year
- 2001
- Type
- article
- Volume
- 42
- Issue
- 1-2
- Pages
- 177-196
- Citations
- 2440
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
2440
OpenAlex
Cite This
Thomas Hofmann
(2001).
Unsupervised Learning by Probabilistic Latent Semantic Analysis.
Machine Learning
, 42
(1-2)
, 177-196.
https://doi.org/10.1023/a:1007617005950
Identifiers
- DOI
- 10.1023/a:1007617005950