Lecture

Vector Space Semantics (and Information Retrieval)

Description

This lecture covers the Vector Space model, indexing, representation function, similarity, and Information Retrieval. It delves into the Bag of Words model, tf-idf weighting schemes, cosine similarity, Okapi BM25, and Precision and Recall. The limitations of the Vector Space model, topic-based models, word embeddings, and the evolution of NLP are also discussed.

Instructors (3)

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Official source

https://mediaspace.epfl.ch/media/0_je3mdw8u

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Ontological neighbourhood

Information engineering

Natural language processing: Topics in natural language processing

Mathematics

Algebra: Linear algebra, Representation theory

Analysis: Functional analysis

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