Information Retrieval Basics: Boolean and Vector Space Models

This lecture covers the basics of information retrieval, focusing on Boolean and Vector Space models. It explains how Boolean retrieval works, the retrieval language syntax, and the computation of similarity in Boolean retrieval. It then delves into Vector Space retrieval, discussing its limitations, the concept of term frequency, inverse document frequency, and query weights. The lecture also provides examples to illustrate the application of these concepts and concludes with an overview of the implementation of information retrieval techniques in Python.