University of Illinois Urbana-Champaign

Text Retrieval and Search Engines

This course is part of Data Mining Specialization

58,669 already enrolled

Gain insight into a topic and learn the fundamentals.
4.5

(947 reviews)

30 hours to complete
3 weeks at 10 hours a week
Flexible schedule
Learn at your own pace
90%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.5

(947 reviews)

30 hours to complete
3 weeks at 10 hours a week
Flexible schedule
Learn at your own pace
90%
Most learners liked this course

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

14 quizzes

Taught in English

See how employees at top companies are mastering in-demand skills

Placeholder

Build your subject-matter expertise

This course is part of the Data Mining Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 7 modules in this course

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.

What's included

2 videos6 readings2 quizzes1 plugin

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

What's included

6 videos1 reading2 quizzes

In this week's lessons, you will learn how the vector space model works in detail, the major heuristics used in designing a retrieval function for ranking documents with respect to a query, and how to implement an information retrieval system (i.e., a search engine), including how to build an inverted index and how to score documents quickly for a query.

What's included

6 videos1 reading2 quizzes

In this week's lessons, you will learn how to evaluate an information retrieval system (a search engine), including the basic measures for evaluating a set of retrieved results and the major measures for evaluating a ranked list, including the average precision (AP) and the normalized discounted cumulative gain (nDCG), and practical issues in evaluation, including statistical significance testing and pooling.

What's included

6 videos2 readings2 quizzes1 programming assignment

In this week's lessons, you will learn probabilistic retrieval models and statistical language models, particularly the detail of the query likelihood retrieval function with two specific smoothing methods, and how the query likelihood retrieval function is connected with the retrieval heuristics used in the vector space model.

What's included

7 videos1 reading2 quizzes

In this week's lessons, you will learn feedback techniques in information retrieval, including the Rocchio feedback method for the vector space model, and a mixture model for feedback with language models. You will also learn how web search engines work, including web crawling, web indexing, and how links between web pages can be leveraged to score web pages.

What's included

8 videos1 reading2 quizzes

In this week's lessons, you will learn how machine learning can be used to combine multiple scoring factors to optimize ranking of documents in web search (i.e., learning to rank), and learn techniques used in recommender systems (also called filtering systems), including content-based recommendation/filtering and collaborative filtering. You will also have a chance to review the entire course.

What's included

10 videos1 reading2 quizzes1 programming assignment1 plugin

Instructor

Instructor ratings
4.4 (85 ratings)
ChengXiang Zhai
University of Illinois Urbana-Champaign
4 Courses103,774 learners

Offered by

Recommended if you're interested in Data Analysis

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

Showing 3 of 947

4.5

947 reviews

  • 5 stars

    65.89%

  • 4 stars

    23.68%

  • 3 stars

    6.73%

  • 2 stars

    1.57%

  • 1 star

    2.10%

SS
4

Reviewed on Mar 27, 2018

GS
5

Reviewed on May 18, 2020

AG
4

Reviewed on Oct 14, 2019

New to Data Analysis? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions