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Book Worm NLP

Book Worm NLP Unlock the stories hidden within your data with Book Worm NLP, a tool designed to bring Natural Language Processing (NLP) closer to everyone. From personal projects to business insights, Book Worm NLP transforms textual analysis into a journey of discovery.

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Overview Book Worm NLP is about more than just data analysis—it's about empowering you to uncover the narratives in your text, whether they're hidden in personal writings, customer feedback, or extensive research papers. Our goal is to make NLP accessible, intuitive, and insightful for everyone, from individuals to businesses and beyond.

Features at a Glance Document Upload: Import txt and PDF files or input text directly. Preprocessing: Clean and prepare your text for deeper analysis. Interactive POS Tagging & Chunking: Visualize sentence structures and extract key insights with color-coded tagging and chunking. nGrams Analysis: Identify common phrases and themes with bigrams and trigrams visualization. Readability Metrics: Tailor your content with readability scores to reach your desired audience. Named Entity Recognition: Discover key entities such as people, places, and organizations in your text. Customizable Lists: Refine your analysis with purpose-built lists, including regional vernacular and domain-specific terms. Why Book Worm NLP? We're here to demystify text analysis, offering a bridge between you and the deeper meanings in your data. With Book Worm NLP, every word counts towards a greater understanding.

Dive Deeper into Features Interactive POS Tagging Dashboard See your text in a new light with our color-coded POS tagging, enhancing your analysis and understanding of language structure.

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Interactive POS Chunk Dataframe Navigate through your text's narrative with dynamic, color-coded POS chunks, uncovering the essence of your analysis in a visually engaging manner.

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nGrams: Uncover Patterns Reveal the heartbeat of your text with our nGrams feature, shedding light on the phrases that define your data and its hidden themes.

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Readability: Communicate Clearly Adjust your text's readability to ensure it resonates with your audience, making your message both clear and engaging.

Named Entity Recognition Map out the landscape of your text with NER, identifying and organizing key entities for a comprehensive overview of your data's focal points.

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Installation Guide Welcome to Book Worm NLP! Follow these steps to get started on your text analysis journey.

Prerequisites Python 3.8 or later Pip (Python package installer) Setting Up a Virtual Environment Open Terminal or Command Prompt

For Mac/Linux, use Terminal.

For Windows, use Command Prompt.

Navigate to Your Project Directory

cd path/to/your/project Create a Virtual Environment

Mac/Linux:

python3 -m venv venv

Windows:

python -m venv venv Activate the Virtual Environment

Mac/Linux: source venv/bin/activate

Windows: .\venv\Scripts\activate

Installing Dependencies/ Install Required Libraries

pip install -r requirements.txt

Additional Setup

For OCR Functionality: Ensure Tesseract OCR is installed on your system and that the pathway to the executable is updated in the ui.py file.

MacOS (using Homebrew) brew install tesseract

Windows: Download from Tesseract's GitHub page and follow the installation instructions.

Getting Started Launch Book Worm NLP To begin your text analysis with Book Worm NLP, navigate to your project directory and execute

python main.py

Dive in and start exploring the depths of your data with Book Worm NLP. Happy analyzing!

MacOS (using Homebrew): brew install tesseract

Windows: Download from Tesseract GitHub and follow the installation guide.

Usage To start Book Worm NLP, navigate to your project directory in the terminal or command prompt and run:

python main.py

Explore your data!

dependency_tree

review sankey

Contributing Book Worm NLP thrives on community contributions. Whether you're interested in adding features, refining our tools, or providing feedback, your insights are invaluable to us. Let's collaborate to enhance Book Worm NLP, making it an even more powerful tool for text analysis.

Got ideas or questions? Reach out at [email protected]. Let's make data analysis accessible to all!

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Contributors

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