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Avis et commentaires pour l'étudiant pour Récupération de texte et moteurs de recherche par Université de l'Illinois à Urbana-Champaign

4.4
487 notes
105 avis

À propos du cours

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....

Meilleurs avis

JH

Sep 21, 2016

Great course for those trying to understand how ro analyse and process text data. It has the right amount of tools to help you understand the basics of information retrieval and search engines.

PM

Aug 29, 2016

A great overview of text retrieval methods. Good coverage of search engines. A longer course will cover search engine better (remember this is a 6 weeker)

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1 - 25 sur 103 Examens pour Récupération de texte et moteurs de recherche

par Karl S

Jul 30, 2018

Although I was very enthusiastic at the beginning of this course, my enthusiasm was soon replaced by disappointment. There were several reasons for my disappointment: First, it is very difficult to understand Prof. ChengXiang Zhai. This is aggravated by the fact that the subtitles of his videos have not been edited and many of these subtitles do not really make any sense. Furthermore, some of the quizzes check on material that is only covered in the week after the quiz. Second, and more importantly, I was disappointed by the explanations offered by Prof. Zhai. Often, he just drops some technical terms without giving any explanation whatsoever. An example in point is his covering of the Kullback-Leibler divergence. He just dropped the name but did not offer any definition or explanation. Unfortunately, there were many more topics that were only covered in such a name dropping way. In the end, I bought myself the book by Stefan Büttcher and the book by Christopher Manning. These are excellent books that were also recommended by Prof. Zhai. For anybody interested in information retrieval I would actually recommend to go directly to these books instead of taking this course.

par Devender B

Feb 14, 2019

Literally this is a dead course. No one is active from course to assist students. You can't complete assignment 1 if you are not good with c++ and STL 'PERIOD'.

Giving up this course

par Bilguun B

Dec 11, 2018

One of the best courses I have taken on Coursera. Really liked how the quizzes were structured!

par Luong A T

Nov 21, 2018

It is a great course, highly recommended for those who wants to work in the AI

par Lena H

Mar 11, 2019

help for building a whole picture about the field

par Amrit S D

Sep 30, 2018

very very good

par Ben L

Dec 25, 2016

Itś a geat course, and the teacher shared his knowlege

par Abhijit D

Apr 04, 2018

Prof Zhai explains very clearly each models with their pros & cons.

par Manoj P

Jul 03, 2016

Very good course for someone who wants to understand how text retrieval works.

par Jose A E H

Sep 21, 2016

Great course for those trying to understand how ro analyse and process text data. It has the right amount of tools to help you understand the basics of information retrieval and search engines.

par Godwin I

Aug 21, 2016

Excellent ! Well organized, presented with aptitude to detail. Definitely will recommend and take further units in this specialization.

Thanks Prof

par Leandro O d N

Oct 03, 2017

Excellent course

par Hafidz J L

May 07, 2018

This advance course just perfect for me who know little bit about advance statistic and linear algebra.

par Wei D

Oct 26, 2017

The novelty of this course is that it not only introduces algorithms, like many other courses, but also focuses on system design issues. You can find algorithms everywhere, but it's not easy to know the system design.

par Andrey N

Jun 10, 2017

Very clear and to the point about complex concepts

par 李元岑

Dec 13, 2016

It's worth to learn!

par Abe G V T S

Oct 15, 2017

This was just the course I needed! Great introduction to the Information Retrieval!

par Hardik J J

Jun 26, 2016

This course is complemented with a software and text (not mandatory) and good explanation with diagrams...

par Vidya S

Jun 24, 2017

Very interesting!

par Isaiah M

Jan 08, 2018

A well put together course, very rigorous and in-depth...

par Codrin K

May 13, 2018

Excellent course. The only request I would have is to make honors programming assignment technology independent (I would have wanted to do it in R) and to add feedback on incorrect answers in quizzes so you can learn more easily from your istakes.

par Rajesh V

Jul 11, 2016

Love the way the professor introduces the concepts, doesn't overwhelm the student!

par Pankaj M

Aug 29, 2016

A great overview of text retrieval methods. Good coverage of search engines. A longer course will cover search engine better (remember this is a 6 weeker)

par Paulina A Q M

Oct 11, 2016

thanks

par RISHABH T

Dec 18, 2017

Good Course