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Text Retrieval and Search Engines, University of Illinois at Urbana-Champaign

4.4
Оценки: 403
Рецензии: 89

Об этом курсе

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....

Лучшие рецензии

автор: 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.

автор: 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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Рецензии: 88

автор: Peter Borysov

Dec 15, 2018

Lectures are fine for those who does not want to read a book and want to get a quick overview. Quizzes are very un-useful and buggy. There are questions presented that are not covered in the section. Programming assignments are optional because instructor did not want to adapt them for Coursera format so that they can be completed using tools of choice.

автор: Bilguun Batsaikhan

Dec 11, 2018

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

автор: Lee Chung Leuk

Nov 21, 2018

Some mistakes in subtitle. and it is better to break down the long videos into smaller sections, illustrate the concepts with more graphs,picture and animation.

автор: Luong Anh Tuan

Nov 21, 2018

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

автор: Amrit Shankar Dutta

Sep 30, 2018

very very good

автор: Phillip J. Vuchetich

Sep 11, 2018

The quiz content is out of sync with the lecture content and has not been fixed after what appears to be 2 years of comments in the course error message board and weekly discussion boards.

автор: Rex Ovie Otavotoma

Aug 30, 2018

The most terrible specialization anyone would ever waste his or her time on! Sometimes i fell asleep lol

Time wasted.

автор: Yongyi Zhou

Aug 24, 2018

I'd appreciate Prof.Zhai's lesson design with robust framework. BUT I really can not accept that the mistake that homework putted in wrong week and STILL NOT FIXED AFTER TWO YEARS!

автор: KM Rao

Aug 24, 2018

Need indetail inputs on algorithm usage and correct MeTA assignments with working scripts. That makes learning a complete curve.

автор: Gustavo Lobo Aguilar

Aug 19, 2018

Great at theory and concept explanation... but just few examples and zero programming applications.