Natural Language Processing
NLP (Labs)
Lab Syllabus
| Sr. No. | Title of the Experiment | CO |
|---|---|---|
| 1 | Study of R tool and basic commands to access text data. | CO1 |
| 2 | Apply various text preprocessing techniques for any given text: (Tokenization and Filtration & Script Validation). | CO2 |
| 3 | Apply various other text preprocessing techniques for any given text. (Stop Word Removal, Lemmatization /Stemming). | CO2 |
| 4 | Implement N-Gram (Bigram) model. | CO2 |
| 5 | Implement Rule-based Part-of-Speech (POS) Tagging. | CO3 |
| 6 | Implement chunking to extract Noun Phrases. | CO3 |
| 7 | Identify semantic relationships between the words from given text (Use WordNet Dictionary). | CO4 |
| 8 | Write a Python program to find synonyms and antonyms of the word "active" using WordNet. | CO4 |
| 9 | Case study on discourse analysis. | CO5 |
| 10 | Perform Name Entity Recognition (NER) on given text. | CO6 |
| 11 | Lab Project: One real life Natural Language application to be implemented (Use standard Datasets available on the web). |
Experiment 1
Study of R tool and basic commands to access text data.
Experiment 2
Apply text preprocessing techniques: tokenization, stop-word removal, and script validation.
Experiment 3
Apply various other text preprocessing techniques for any given text.
Experiment 4
Implement N-Gram (Bigram) model.
Experiment 5
Implement Rule-based Part-of-Speech (POS) Tagging.
Experiment 6
Implement chunking to extract Noun Phrases.
Experiment 7
Identify semantic relationships between the words from given text.
Experiment 8
Write a Python program to find synonyms and antonyms of the word active using WordNet.
Experiment 9
Case study on discourse analysis.