Natural Language Processing Web Application Example

This is a simple web application that demonstrates various Natural Language Processing (NLP) techniques such as Sentiment Analysis, Entity Extraction, Text Summarization, and Machine Translation.

Required Libraries

• Streamlit
• Pandas
• Matplotlib
• TextBlob
• NLTK
• Gensim
• Spacy
• Googletrans

These libraries can be installed using pip.

Running the Application

1. Clone the repository.
2. Install the required libraries.
3. Open a command prompt or terminal and navigate to the folder containing the code.
4. Run the following command: streamlit run main.py
5. The application will open in a new tab of your default web browser.

Usage

The application is a simple web form that asks the user to enter the text they would like to analyze. The user can then select the NLP task they would like to perform, which includes Sentiment Analysis, Entity Extraction, Text Summarization, and Machine Translation.

Sentiment Analysis

This NLP task analyzes the sentiment of the input text and displays the sentiment scores of each sentence in a line graph. It also displays the overall sentiment polarity and subjectivity of the entire text.

Entity Extraction

This NLP task identifies the named entities in the input text and their types. It displays the entities of each type in a separate section.

Text Summarization

This NLP task summarizes the input text and displays it in a separate section.

Machine Translation

This NLP task translates the input text from English to either Hindi or Marathi based on the user's selection. The translated text is displayed in a separate section.

Currently Support

• English
• Hindi

Acknowledgements

This application is created using various NLP libraries and techniques, including TextBlob, NLTK, Gensim, Spacy, and Googletrans. The code is based on tutorials and examples from the documentation of these libraries.