關於此課程：This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists. Empowered by bringing lecture notes together with lab sessions based on the y-TextMiner toolkit developed for the class, learners will be able to develop interesting text mining applications.

製作方： Yonsei University

教學方： Min Song, Professor
Library & Information Technology

級別	中級
語言	English, 字幕：Spanish, Chinese (Simplified)
如何通過	通過所有計分作業以完成課程。
用戶評分	4.1 星平均用戶評分 4.1查看學生的留言

授課大綱

第 1 週

Course Logistics and the Text Mining Tool for the Course

4 個視頻, 1 個閱讀材料

視頻: 1.2 Explanations of the y-TextMiner package and the datasets
視頻: 1.3 How-to-do: workspace installation and setup
視頻: 1.4 How-to-use: the y-TextMiner package (download it at http://informatics.yonsei.ac.kr/yTextMiner/yTextMiner1.2.zip)
Reading: What is Text Mining?
Peer Review: y-TextMiner installation and a simple Java program

第 2 週

Text Preprocessing

5 個視頻, 1 個閱讀材料

視頻: 2.2 What is text mining?
視頻: 2.3 Description of preprocessing techniques
視頻: 2.4 How-to-do: normalization including tokenization and lemmatization
視頻: 2.5 How-to-do: N-Grams
Reading: Text Preprocessing
Peer Review: Preprocessing Practice

第 3 週

Text Analysis Techniques

6 個視頻, 2 個閱讀材料

視頻: 3.2 Explanations of named entity recognition
視頻: 3.3 Explanations of dependency parsing
視頻: 3.4 How-to-do: stopword removal and stemming
視頻: 3.5 How-to-do: NER and POS Tagging
視頻: 3.6 How-to-do: constituency and dependency parsing
Reading: Stemming and Lemmatization
Reading: Named Entity Recognition

已評分: Text Analysis Practice

第 4 週

Term Weighting and Document Classification

5 個視頻, 2 個閱讀材料

視頻: 4.2 Explanations of document classification
視頻: 4.3 Explanations of sentiment analysis
視頻: 4.4 How-to-do: computation of tf*idf weighting
視頻: 4.5 How-to-do: classification with Logistic Regression
Reading: Text Classification
Reading: TF-IDF

已評分: Document Classification Practice

第 5 週

Sentiment Analysis

6 個視頻, 1 個閱讀材料

視頻: 5.2 Explanations of sentiment analysis with unsupervised learning
視頻: 5.3 Explanations of sentiment analysis with CoreNLP, LingPipe and SentiWordNet
視頻: 5.4 How-to-do: sentiment analysis with CoreNLP
視頻: 5.5 How-to-do: sentiment analysis with LingPipe
視頻: 5.6 How-to-do: sentiment analysis with SentiWordNet
Reading: Opinion mining and sentiment analysis by Bo Pang and Lillian Lee

已評分: Sentiment Analysis Practice

第 6 週

Topic Modeling

5 個視頻, 1 個閱讀材料

視頻: 6.2 Explanations of LDA and DMR
視頻: 6.3 Description of Topic Modeling with Mallet
視頻: 6.4 How-to-do: LDA
視頻: 6.5 How-to-do: DMR
Reading: Introduction to Probabilistic Topic Models by David Blei

已評分: Topic Modeling Practice

常見問題解答

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運作方式

Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

製作方

Yonsei University

Yonsei University was established in 1885 and is the oldest private university in Korea. Yonsei’s main campus is situated minutes away from the economic, political, and cultural centers of Seoul’s metropolitan downtown. Yonsei has 3,500 eminent faculty members who are conducting cutting-edge research across all academic disciplines. There are 18 graduate schools, 22 colleges and 133 subsidiary institutions hosting a selective pool of students from around the world. Yonsei is proud of its history and reputation as a leading institution of higher education and research in Asia.

評分和審閱

已評分 4.1，總共 5 個 36 評分