|
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 |