Information Retrieval: Basics and Techniques

This lecture covers the fundamentals of Information Retrieval (IR), including the vector space model, indexing terms, weighting schemes like tf.idf and Okapi BM25, cosine proximity measure, representing queries, and evaluating IR systems. It delves into the limitations of the vector space model, distributional semantics, and advanced models. Key topics include tokenization, filtering, Bag of Words model, and the importance of good indexing for IR system performance.