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.
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Habilidades que obtendrás
Universidad de Illinois en Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
- 5 stars65,57 %
- 4 stars23,93 %
- 3 stars6,77 %
- 2 stars1,63 %
- 1 star2,07 %
Principales reseñas sobre TEXT RETRIEVAL AND SEARCH ENGINES
Excellent Course for Computer Science Enthusiastic.
Must and Highly recommend course for all Computer Science and Information technology Aspirant
I have learned a lot of concepts through this course, but at a shallow level. It is a great introduction course to IR. It can be improved by adding more programming tasks for hands-on exercise
However the prof/instructor should practice not pausing so much when explaining the concepts/contents
This course is complemented with a software and text (not mandatory) and good explanation with diagrams...
Acerca de Programa especializado: minería de datos
The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp.
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