Скачать или смотреть Lesson 6.5: Recommender Systems: Content-Based Filtering - Part 1 - Text Retrieval and Search

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Lesson 6.5: Recommender Systems: Content-Based Filtering - Part 1 - Text Retrieval and Search Engines
Data Mining Specialization
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.
Information Retrieval (IR), Document Retrieval, Machine Learning, Recommender Systems
Excellent ! Well organized, presented with aptitude to detail. Definitely will recommend and take further units in this specialization. Thanks Prof,Excellent Course for Computer Science Enthusiastic. Must and Highly recommend course for all Computer Science and Information technology Aspirant
In this week's lessons, you will learn how machine learning can be used to combine multiple scoring factors to optimize ranking of documents in web search (i.e., learning to rank), and learn techniques used in recommender systems (also called filtering systems), including content-based recommendation/filtering and collaborative filtering. You will also have a chance to review the entire course.
Lesson 6.5: Recommender Systems: Content-Based Filtering - Part 1 - Text Retrieval and Search Engines
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