Text Retrieval and Search Engines

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course.

During this week's lessons, you will learn natural language processing techniques, the foundation for text-processing applications, the concept of a retrieval model, and the basic idea of the vector space model.

In this week's lessons, you will learn how the vector space model works in detail, major heuristics for designing retrieval functions, and how to implement an information retrieval system including inverted index building and document scoring.

In this week's lessons, you will learn how to evaluate an information retrieval system, including basic measures for evaluating retrieved results and major measures for evaluating ranked lists, including AP and nDCG, and practical evaluation issues.

In this week's lessons, you will learn probabilistic retrieval models and statistical language models, particularly the query likelihood retrieval function with specific smoothing methods, and connections with vector space model retrieval heuristics.

In this week's lessons, you will learn feedback techniques in information retrieval, including Rocchio feedback and language model feedback methods. You will also learn about web search engines, including crawling, indexing, and link analysis.

In this week's lessons, you will learn about machine learning for document ranking optimization, recommender systems including content-based and collaborative filtering, and review the entire course.