Text-Mining & Social Networks
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Contents:
1. Basics in Text-Mining
2. Spell Checker
3. Text Classificaton
4. Document Similarity
5. Topic Modelling
6. Resources
7. Glossary
Text-Mining & Social Networks
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Text-Mining
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Text-Mining
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This documentation summarises various text-mining techniques in Python.
Contents:
1. Basics in Text-Mining
1.1. Tokenisation
1.2. Vectorization
2. Spell Checker
2.1. Jaccard Distance on Trigram
2.2. Jaccard Distance on 4-gram
2.3. Edit Distance
3. Text Classificaton
3.1. Add New Features to Vectorizer
3.2. Multi-Nominal Naive Bayes & CountVectorizer
3.3. Multi-Nominal Naive Bayes & TfidfVectorizer
3.4. Support Vector Machine & TfidfVectorizer
3.5. Logistic Regression & TfidfVectorizer
3.6. Logistic Regression & CountVectorizer
4. Document Similarity
4.1. Create a Similiarity Function Btw Two Documents
4.2. Assign Scores to New Documents
4.3. Calculate Accuarcy Score
5. Topic Modelling
5.1. Latent Dirichlet Allocation
6. Resources
7. Glossary
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