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 | 英語（English）, 字幕：西班牙語（Spanish）, 中文（簡體） |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
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?
- 同学互评: 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
- 同学互评: 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
運作方式
课程作业
每门课程都像是一本互动的教科书，具有预先录制的视频、测验和项目。
来自同学的帮助
与其他成千上万的学生相联系，对想法进行辩论，讨论课程材料，并寻求帮助来掌握概念。
证书
获得正式认证的作业，并与朋友、同事和雇主分享您的成功。
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
Excellent theory and hands-on lab codes. It'd be great if you could also cover how-to in other relevant programming languages using R or Python.
Excellent course !!
Thanks