UIUC - Text Retrieval and Search Engines
- Offered byCoursera
Text Retrieval and Search Engines at Coursera Overview
Duration | 31 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Text Retrieval and Search Engines at Coursera Highlights
- 50% started a new career after completing these courses.
- 60% got a tangible career benefit from this course.
- 25% got a pay increase or promotion.
- Earn a shareable certificate upon completion.
Text Retrieval and Search Engines at Coursera Course details
- Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people¢??s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.
- This course will cover search engine technologies, which play an important role in any data mining applications involving text data for two reasons. First, while the raw data may be large for any particular problem, it is often a relatively small subset of the data that are relevant, and a search engine is an essential tool for quickly discovering a small subset of relevant text data in a large text collection. Second, search engines are needed to help analysts interpret any patterns discovered in the data by allowing them to examine the relevant original text data to make sense of any discovered pattern. You will learn the basic concepts, principles, and the major techniques in text retrieval, which is the underlying science of search engines.
Text Retrieval and Search Engines at Coursera Curriculum
Orientation
Course Welcome Video
Course Introduction Video
Welcome to Text Retrieval and Search Engines!
Syllabus
About the Discussion Forums
Updating your Profile
Social Media
Course Errata
Orientation Quiz
Pre-Quiz
Lesson 1.1: Natural Language Content Analysis
Lesson 1.2: Text Access
Lesson 1.3: Text Retrieval Problem
Lesson 1.4: Overview of Text Retrieval Methods
Lesson 1.5: Vector Space Model - Basic Idea
Lesson 1.6: Vector Space Retrieval Model - Simplest Instantiation
Week 1 Overview
Week 1 Practice Quiz
Week 1 Quiz
Week 2
Lesson 2.1: Vector Space Model - Improved Instantiation
Lesson 2.2: TF Transformation
Lesson 2.3: Doc Length Normalization
Lesson 2.4: Implementation of TR Systems
Lesson 2.5: System Implementation - Inverted Index Construction
Lesson 2.6: System Implementation - Fast Search
Week 2 Overview
Week 2 Practice Quiz
Week 2 Quiz
Week 3
Lesson 3.1: Evaluation of TR Systems
Lesson 3.2: Evaluation of TR Systems - Basic Measures
Lesson 3.3: Evaluation of TR Systems - Evaluating Ranked Lists - Part 1
Lesson 3.4: Evaluation of TR Systems - Evaluating Ranked Lists - Part 2
Lesson 3.5: Evaluation of TR Systems - Multi-Level Judgements
Lesson 3.6: Evaluation of TR Systems - Practical Issues
Week 3 Overview
Programming Assignments Overview
Week 3 Practice Quiz
Week 3 Quiz
Week 4
Lesson 4.1: Probabilistic Retrieval Model - Basic Idea
Lesson 4.2: Statistical Language Model
Lesson 4.3: Query Likelihood Retrieval Function
Lesson 4.4: Statistical Language Model - Part 1
Lesson 4.5: Statistical Language Model - Part 2
Lesson 4.6: Smoothing Methods - Part 1
Lesson 4.7: Smoothing Methods - Part 2
Week 4 Overview
Week 4 Practice Quiz
Week 4 Quiz
Week 5
Lesson 5.1: Feedback in Text Retrieval
Lesson 5.2: Feedback in Vector Space Model - Rocchio
Lesson 5.3: Feedback in Text Retrieval - Feedback in LM
Lesson 5.4: Web Search: Introduction & Web Crawler
Lesson 5.5: Web Indexing
Lesson 5.6: Link Analysis - Part 1
Lesson 5.7: Link Analysis - Part 2
Lesson 5.8: Link Analysis - Part 3
Week 5 Overview
Week 5 Practice Quiz
Week 5 Quiz
Week 6
Lesson 6.1: Learning to Rank - Part 1
Lesson 6.2: Learning to Rank - Part 2
Lesson 6.3: Learning to Rank - Part 3
Lesson 6.4: Future of Web Search
Lesson 6.5: Recommender Systems: Content-Based Filtering - Part 1
Lesson 6.6: Recommender Systems: Content-Based Filtering - Part 2
Lesson 6.7: Recommender Systems: Collaborative Filtering - Part 1
Lesson 6.8: Recommender Systems: Collaborative Filtering - Part 2
Lesson 6.9: Recommender Systems: Collaborative Filtering - Part 3
Lesson 6.10: Course Summary
Week 6 Overview
Week 6 Practice Quiz
Week 6 Quiz
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