Search Engines for Web and Enterprise Data
Learn the technologies behind web and search engines, including document indexing, ranking, and user intent understanding. Explore advanced applications like recommendation systems and summarization. Real-life examples and case studies reinforce understanding of search algorithms.
This course introduces the technologies behind web and search engines, including document indexing, searching and ranking. You will also learn different performance metrics for evaluating search quality, methods for understanding user intent and document semantics, and advanced applications including recommendation systems and summarization. Real-life examples and case studies are provided to reinforce the understanding of search algorithms.
What you will learn
Introduction to Search Engines for Web and Enterprise Data
Welcome to the first module of this course! In this module, you will learn: (1) The major tasks involved in web search. (2) The history, evolution, impacts and challenges of web search engine.
Search Engine Business Model
In this module, you will learn: (1) Different business models of web search engine.
TFxIDF
In this module, you will learn: (1) Different information retrieval models, Boolean Models and Statistical models. (2) How to determine important words in a document using TFxIDF.
Vector Space Model
In this module, you will learn: (1) How to represent a document/query as a vector of keywords. 2) How to determine the degree of similarity between a pair of vectors using different similarity measures, including Inner Product, Cosine Similarity, Jaccard Coefficient, Dice Coefficient.
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