À propos de ce cours : 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.
Créé par : Yonsei University
Enseigné par : Min Song, Professor
Library & Information Technology
| Niveau | Intermédiaire |
| Langue | English, Sous-titres : Spanish, Chinese (Simplified) |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
| Notes des utilisateurs |
Programme de cours
SEMAINE 1
Course Logistics and the Text Mining Tool for the Course
4 vidéos, 1 lecture
- Vidéo: 1.2 Explanations of the y-TextMiner package and the datasets
- Vidéo: 1.3 How-to-do: workspace installation and setup
- Vidéo: 1.4 How-to-use: the y-TextMiner package (download it at http://informatics.yonsei.ac.kr/yTextMiner/yTextMiner.zip)
- Reading: What is Text Mining?
- Peer Review: y-TextMiner installation and a simple Java program
SEMAINE 2
Text Preprocessing
5 vidéos, 1 lecture
- Vidéo: 2.2 What is text mining?
- Vidéo: 2.3 Description of preprocessing techniques
- Vidéo: 2.4 How-to-do: normalization including tokenization and lemmatization
- Vidéo: 2.5 How-to-do: N-Grams
- Reading: Text Preprocessing
- Peer Review: Preprocessing Practice
SEMAINE 3
Text Analysis Techniques
6 vidéos, 2 lectures
- Vidéo: 3.2 Explanations of named entity recognition
- Vidéo: 3.3 Explanations of dependency parsing
- Vidéo: 3.4 How-to-do: stopword removal and stemming
- Vidéo: 3.5 How-to-do: NER and POS Tagging
- Vidéo: 3.6 How-to-do: constituency and dependency parsing
- Reading: Stemming and Lemmatization
- Reading: Named Entity Recognition
Noté: Text Analysis Practice
SEMAINE 4
Term Weighting and Document Classification
5 vidéos, 2 lectures
- Vidéo: 4.2 Explanations of document classification
- Vidéo: 4.3 Explanations of sentiment analysis
- Vidéo: 4.4 How-to-do: computation of tf*idf weighting
- Vidéo: 4.5 How-to-do: classification with Logistic Regression
- Reading: Text Classification
- Reading: TF-IDF
Noté: Document Classification Practice
SEMAINE 5
Sentiment Analysis
6 vidéos, 1 lecture
- Vidéo: 5.2 Explanations of sentiment analysis with unsupervised learning
- Vidéo: 5.3 Explanations of sentiment analysis with CoreNLP, LingPipe and SentiWordNet
- Vidéo: 5.4 How-to-do: sentiment analysis with CoreNLP
- Vidéo: 5.5 How-to-do: sentiment analysis with LingPipe
- Vidéo: 5.6 How-to-do: sentiment analysis with SentiWordNet
- Reading: Opinion mining and sentiment analysis by Bo Pang and Lillian Lee
Noté: Sentiment Analysis Practice
SEMAINE 6
Topic Modeling
5 vidéos, 1 lecture
- Vidéo: 6.2 Explanations of LDA and DMR
- Vidéo: 6.3 Description of Topic Modeling with Mallet
- Vidéo: 6.4 How-to-do: LDA
- Vidéo: 6.5 How-to-do: DMR
- Reading: Introduction to Probabilistic Topic Models by David Blei
Noté: Topic Modeling Practice
FAQ
Comment cela fonctionne
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
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Créateurs
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.
Notation et examens
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 !!
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Thanks