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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データマイニング 専門講座イリノイ大学アーバナ・シャンペーン校（University of Illinois at Urbana-Champaign）このコースについて
18,262 最近の表示
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共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における6の2コース
約31時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, 英語, スペイン語
習得するスキル
- Information Retrieval (IR)
- Document Retrieval
- Machine Learning
- Recommender Systems
柔軟性のある期限
スケジュールに従って期限をリセットします。
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における6の2コース
約31時間で修了
英語
字幕：アラビア語, フランス語, ポルトガル語（ヨーロッパ）, イタリア語, ベトナム語, 韓国語, ドイツ語, ロシア語, 英語, スペイン語
提供：
イリノイ大学アーバナ・シャンペーン校（University of Illinois at 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.
シラバス - 本コースの学習内容
2時間で修了
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時間で修了
2件のビデオ （合計15分）, 6 学習用教材, 2 個のテスト
4時間で修了
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時間で修了
6件のビデオ （合計94分）, 1 学習用教材, 2 個のテスト
4時間で修了
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時間で修了
6件のビデオ （合計102分）, 1 学習用教材, 2 個のテスト
7時間で修了
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時間で修了
6件のビデオ （合計75分）, 2 学習用教材, 3 個のテスト
4時間で修了
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時間で修了
7件のビデオ （合計88分）, 1 学習用教材, 2 個のテスト
レビュー
TEXT RETRIEVAL AND SEARCH ENGINES からの人気レビュー
JHにより2016年9月20日
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.
SXにより2018年3月27日
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
JWにより2020年6月25日
I will keep the last star for not using a more cutting edge programming language, e.g. python. MeTa is not really helpful in the business world and that discounts the value of this course.
WPにより2017年5月27日
I found that there were a lot of mathematical function in this course. I need to see the examples of how are those functions applied in the real programming which support the business.
データマイニング 専門講座について
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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