|
Week - 1 |
Introduction: What is Semantic Analysis? NLP and Applications |
|
Week - 2 |
Introduction to Text Mining with R: Basic Functions |
|
Week - 3 |
Tokenization, Stop Words, Lemmatisation |
|
Week - 4 |
Word Frequency and TF-IDF |
|
Week - 5 |
N-grams and Semantic Patterns |
|
Week - 6 |
Sentiment Analysis and Dictionary-Based Approaches |
|
Week - 7 |
Sentiment Analysis and Machine Learning Based Approaches |
|
Week - 8 |
Semantic Networks and Word Association Maps |
|
Week - 9 |
Word Embedding: Word2Vec, GloVe |
|
Week - 10 |
Semantic Similarity Measures |
|
Week - 11 |
Topic Modelling: LDA (Latent Dirichlet Allocation) |
|
Week - 12 |
Change of Meaning in Texts and Contexts of Use |
|
Week - 13 |
Visualisation in textual data analysis |
|
Week - 14 |
Project Presentations |