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.
Este curso forma parte de Programa especializado: minería de datos
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Programa especializado: minería de datos Universidad de Illinois en Urbana-ChampaignAcerca de este Curso
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Curso 2 de 6 en
Aprox. 31 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
Habilidades que obtendrás
- Information Retrieval (IR)
- Document Retrieval
- Machine Learning
- Recommender Systems
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 2 de 6 en
Aprox. 31 horas para completar
Inglés (English)
Subtítulos: Árabe (Arabic), Francés (French), Portugués (europeo), Italiano, Vietnamita, Coreano, Alemán (German), Ruso (Russian), Inglés (English), Español (Spanish)
ofrecido por
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.
Programa - Qué aprenderás en este curso
2 horas para completar
Orientation
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.
2 horas para completar
2 videos (Total 15 minutos), 6 lecturas, 2 cuestionarios
4 horas para completar
Week 1
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.
4 horas para completar
6 videos (Total 94 minutos), 1 lectura, 2 cuestionarios
4 horas para completar
Week 2
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.
4 horas para completar
6 videos (Total 102 minutos), 1 lectura, 2 cuestionarios
7 horas para completar
Week 3
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.
7 horas para completar
6 videos (Total 75 minutos), 2 lecturas, 3 cuestionarios
4 horas para completar
Week 4
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.
4 horas para completar
7 videos (Total 88 minutos), 1 lectura, 2 cuestionarios
Reseñas
- 5 stars65,45 %
- 4 stars23,98 %
- 3 stars6,82 %
- 2 stars1,65 %
- 1 star2,09 %
Principales reseñas sobre TEXT RETRIEVAL AND SEARCH ENGINES
por GI20 de ago. de 2016
Excellent ! Well organized, presented with aptitude to detail. Definitely will recommend and take further units in this specialization.
Thanks Prof
por LL20 de nov. de 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.
por HJ25 de jun. de 2016
This course is complemented with a software and text (not mandatory) and good explanation with diagrams...
por GS18 de may. de 2020
A bit difficult to complete as the Quiz questions were tougher. But when you go through all, you might feel good.
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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