Probabilistic latent semantic analysis

Applied sciences
Information engineering
Natural language processing
Topic modelling

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Related lectures (32)

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Text Models: Word Embeddings and Topic Models

Explores word embeddings, topic models, Word2vec, Bayesian Networks, and inference methods like Gibbs sampling.

Understanding Preference Elicitation

Explores preference elicitation, latent variables, and the impact of external events on decision-making.

Variational Inference and Neural Networks

Covers variational inference and neural networks for classification tasks.

Latent variables in choice models: Optima case study

Explores the Optima case study, analyzing attitudes and mode choice.

Latent Semantic Indexing: Concepts and Applications

Explores latent semantic indexing, vocabulary construction, document matrix creation, query transformation, and document retrieval using cosine similarity.

Latent Dirichlet Allocation

Covers Latent Dirichlet Allocation, a state-of-the-art method for concept extraction using a probabilistic generative model.

Latent semantic indexing: inverted files

Explores term-offset indices in inverted files and relevance feedback solutions.

Topic Models

Introduces topic models, covering clustering, GMM, LDA, Dirichlet distribution, and variational inference.

Latent Semantic Indexing

Covers Latent Semantic Indexing, a method to improve information retrieval by mapping documents and queries into a lower-dimensional concept space.

Optimization in Machine Learning

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.