Applications of N-grams

N-grams are used in various NLP tasks to model the probability of word sequences, providing insight into local context and word dependencies.

1. Language Modeling:

   N-grams can predict the next word in a sequence based on the preceding words, useful in tasks like text generation and autocompletion.

2. Machine Translation:

   Bigrams and trigrams help identify common word phrases and their translations across different languages.

3. Text Summarization:

   By analysing n-grams, key phrases and concepts can be extracted from a larger text for summarisation.

4. Spam Filtering:

   Frequent n-grams in spam emails can help identify and filter out unwanted messages.

5. Topic Modelling:

   Bigrams improve the accuracy of topic identification, helping to clarify complex phrases. For instance:

   • Social vs. Social Media, Social Media Analytics
   • Data vs. Data Mining, Data Science

6. Sentiment Analysis:

   Incorporating n-grams allows for a more nuanced understanding of sentiment in text, particularly through capturing combinations of words that convey specific emotions.