Text Retrieval and Search Engines

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6/10 stars
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Course Details

Cost

FREE,
Add a Verified Certificate for $79

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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4721 reviews

Course Description

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. S... 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 course image
Reviews 6/10 stars
5 Reviews for Text Retrieval and Search Engines

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Mike Turner profile image
Mike Turner profile image
2/10 starsTaking Now
  • 3 reviews
  • 2 completed
2 years, 11 months ago
I was originally excited to get a decent introduction to text retrieval methods in order to apply them in my current career, but this course falls very short of properly educating people on this subject and I would recommend skipping it. Here is a step-step review of it. 1 - The lectures The lectures and lecturer are actually decent, they introduce the concepts in a fairly clear way and cover a lot of good ground. I do not have an issue with the way this is presented in lecture. 2 - The assignments (poor quality) In this course there are quizzes and programming assignments, and the programming assignments are optional. This is not good, because programming assignments are how you learn. The programming assignments that do exist are of very poor quality. The first assignment is a step by step set of instructions to use a text retrieval toolkit (meta-toolkit.org) to do simple things, it doesn't make you program - ... I was originally excited to get a decent introduction to text retrieval methods in order to apply them in my current career, but this course falls very short of properly educating people on this subject and I would recommend skipping it. Here is a step-step review of it. 1 - The lectures The lectures and lecturer are actually decent, they introduce the concepts in a fairly clear way and cover a lot of good ground. I do not have an issue with the way this is presented in lecture. 2 - The assignments (poor quality) In this course there are quizzes and programming assignments, and the programming assignments are optional. This is not good, because programming assignments are how you learn. The programming assignments that do exist are of very poor quality. The first assignment is a step by step set of instructions to use a text retrieval toolkit (meta-toolkit.org) to do simple things, it doesn't make you program - only follow directions so there's little critical thinking involved. Secondly, it uses a very niche C++ NLP tool the instructor's grad student created called MeTA. It is not widely used and therefore the support & knowledgebase surrounding it is mostly non-existant and nobody representing the course answers the course forum, so if things go wrong, it is hard to find an answer as to why. Thirdly, currently the assignment files have not been updated in a long time, and they do not work correctly with the current version of MeTA (2.30) and thus you cannot complete the assignment without spending a lot of hours figuring out how to update the data provided YOURSELF to work correctly with the current version of MeTA. So the course's assignments are hard to complete due to negligence on the instructor's part. The second assignment is better, but also has recommendations out of date with the current version of MeTA. Overall I'd say this course suffers from 3 main things that make it not worth taking - It has you use a tool used by almost nobody created by the instructor's grad student that has zero support instead of better many supported tools out there. - Instructors & Course Representatives have clearly neglected the content & it doesn't work correctly forcing the student to fix the instructor's errors in the assignment content. - The programming challenges don't make you think too much, thus not giving you a very good hands on intro to the subject matter. There are better courses that teach this subject out there, and I'd recommend you skip this one in favor of one that uses better supported tools and better teaches hands on learning.
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Kristina Šekrst profile image
Kristina Šekrst profile image
8/10 starsCompleted
  • 102 reviews
  • 102 completed
4 years ago
I'm encouraging more programming assignments dealing with NLP, and a bit smaller focus on C++ and more R/Py support. It was a fun experience, and I hope that the theoretical approach will slowly turn into a combination of theory and practice.
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Richard Taylor profile image
Richard Taylor profile image
4/10 starsCompleted
  • 29 reviews
  • 28 completed
4 years, 3 months ago
This course has good content but the way the content is presented is just terrible. The instructor doesn't care about making the concepts simple he just mumbles around formulas and papers without examples. As any student and instructor knows complex subjects can be explained if you create simple examples to show how things work in practice this course doesn't care about that. I also disliked the programming assignment that uses a very strange platform and asks the students to complete very simple tasks without any interesting goal. I liked the topics a lot and I disliked how they were presented even more.
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Greg Hamel profile image
Greg Hamel profile image
6/10 stars
  • 116 reviews
  • 107 completed
4 years, 5 months ago
Text Retrieval and Search Engines is the second course in Coursera's new data mining specialization offered by the University of Illinois at Urbana-Champaign. The course covers a variety of topics in text data mining and natural language processing including text retrieval, query ranking and evaluation methods, methods and the basics of recommender systems. Grading is based entirely on 4 weekly quizzes comprised of 10 multiple choice questions. You only get 1 attempt on the quizzes. The weekly content in Text Retrieval and Search Engines consists of around 10 video lectures that range from 5 to 20 minutes followed by a short 10 question quiz. If that sounds like a lot of lecture per question, it is, and there are no in-lecture quizzes to reinforce concepts as you go along. The lectures themselves are definitely a step up from the first course in the specialization, Pattern Discovery in Data Mining. The professor isn't hard to unde... Text Retrieval and Search Engines is the second course in Coursera's new data mining specialization offered by the University of Illinois at Urbana-Champaign. The course covers a variety of topics in text data mining and natural language processing including text retrieval, query ranking and evaluation methods, methods and the basics of recommender systems. Grading is based entirely on 4 weekly quizzes comprised of 10 multiple choice questions. You only get 1 attempt on the quizzes. The weekly content in Text Retrieval and Search Engines consists of around 10 video lectures that range from 5 to 20 minutes followed by a short 10 question quiz. If that sounds like a lot of lecture per question, it is, and there are no in-lecture quizzes to reinforce concepts as you go along. The lectures themselves are definitely a step up from the first course in the specialization, Pattern Discovery in Data Mining. The professor isn't hard to understand this time around and he explains concepts well enough to grasp them without having to re-watch videos. As with many of Coursera's other 4-week specializations, however, lectures sometimes turn into information dumps where the professor ends up reading off slides. The course does have a C++ programming assignment which was nice to see. Text Retrieval and Search Engines is a decent course that is worth a look if you are interested in text data mining and search engines. Although the lectures lackluster, they have some good information. If you're planning on getting a verified certificate, it is a good idea to try the practice quizzes before submitting the real one. I give this course 2.75 out of 5 stars: Fair.
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Student profile image
Student profile image

Student

8/10 starsCompleted
4 years, 5 months ago
The course has a great content on various popular retrieval methods used in practical search engines. It enables you to understand complex search engines retrieval methods step-by-step by building each component every lecture. Apart from quizzes you can optionally also work on practical aspects by participating in programming assignments. The last search engine competition is very exciting and you learn how each component is very critical to improve your search engine accuracy. Overall its a great course.
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