Latent Semantic Indexing

Related lectures (28)

Page 3 of 3

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

Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.

Explores handling text data, deriving clean datasets from unstructured text, and various text analysis techniques.

Introduces Latent Dirichlet Allocation for topic modeling in documents, discussing its process, applications, and limitations.

Covers document retrieval, classification, sentiment analysis, and topic detection using TF-IDF matrices and contextualized word vectors.

Introduces the basics of text data processing, covering document retrieval, classification, sentiment analysis, and topic detection.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.

Covers calculations in coordinates for vectors, including bases, scalar product, and determinants, with geometric interpretations and examples.