Lectures related to Lexical semantics

Explores lexical semantics, word sense, semantic relations, and WordNet, highlighting applications in language engineering and information retrieval.

Covers the basics of Natural Language Processing, including challenges, linguistic processing levels, and the impact of power laws.

Explores Part-of-Speech tagging using probabilistic models like Hidden Markov Models and discusses the resolution of lexical ambiguities.

Explores words, tokens, and language models in NLP, covering challenges in defining them, lexicon usage, n-grams, and probability estimation.

Explores the Vector Space model, Bag of Words, tf-idf, cosine similarity, Okapi BM25, and Precision and Recall in Information Retrieval.