NLP CoURSE OUTLINE

Natural Language Processing
Topics:
1. CFG
2. Tokenization
2.1. Generic
2.2. Special Tokens
2.2.1. Named Entity Recognition
2.2.2. Word Normalization
3. String Searching
3.1. Abocrasik Algorithm
4. Parts of speech tagging.
4.1. Hidden Markov Model
5. Handling Morphological Variations
5.1. Algorithms
5.1.1. Stemming(Suffix striping)
5.1.2. Stochastic Algorithms
5.1.3. Bruteforce Algorithm
5.1.4. Lemitization
5.1.5. Hybrid Approaches
5.1.5.1. Suffix Tree Algo
5.1.5.2. Affix Statement
5.2. Measurement of stemming algorithm
5.2.1. Under
5.2.2. Over
6. Vector Spaces in NLP
6.1. Weighing Formula
6.2. Similarity
6.2.1. For Binary data
6.2.2. For Ordinal data
6.2.3. For Categorical data
6.2.4. For Quantitative data
6.3. SVD
6.3.1. Term Document Matrix
6.3.2. Truncated SVD
7. Speech to Text
8. Text To Speech

Dated 28-September-2011


Regards
Arsalan Shahid