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UppuluriKalyani / ML-Nexus

ML Nexus is an open-source collection of machine learning projects, covering topics like neural networks, computer vision, and NLP. Whether you're a beginner or expert, contribute, collaborate, and grow together in the world of AI. Join us to shape the future of machine learning!
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Feature request: News Articles Category Prediction #177

Open pratikwayal01 opened 2 days ago

pratikwayal01 commented 2 days ago

Feature Request: News Articles Category Prediction

Summary: A feature to predict the category of a news article (such as Sports, Politics, Entertainment, Technology, etc.) based on its content. This will enhance the platform's ability to automatically categorize news content and make it easier for users to find relevant articles.

Details:

  1. Objective: Implement a model that can predict the category of a news article using its text. The model should be able to handle various article topics and assign categories like:

    • Politics
    • Sports
    • Entertainment
    • Technology
    • Science
    • Health
    • Business
    • World

  2. Requirements:

    • A dataset of categorized news articles for training the model.
    • A pre-trained Natural Language Processing (NLP) model for text classification (such as BERT, GPT, or similar models).
    • Ability to integrate the model with the existing backend, ensuring real-time predictions when new articles are uploaded or written.

  3. Proposed Approach:

    • Preprocess the articles by removing unnecessary metadata, cleaning text, and tokenization.
    • Train an NLP-based classifier (e.g., Logistic Regression, Random Forest, or a deep learning model like a Transformer) on the labeled dataset of news articles.
    • Evaluate the model’s accuracy using standard metrics like F1-score, precision, and recall.
    • Integrate the trained model into the system, enabling automatic categorization of articles at the time of submission.
    • Provide an API for querying the model to get category predictions.

  4. Benefits:

    • Improves user experience by categorizing articles accurately and automatically.
    • Enhances the discoverability of news articles based on categories.
    • Reduces manual effort in tagging and organizing articles.

  5. Possible Challenges:

    • Data availability: Large and diverse datasets are required for accurate prediction across multiple categories.

    • Handling ambiguous content that may fit into multiple categories.

github-actions[bot] commented 2 days ago

Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. Your contributions are highly appreciated! 😊

JahnaviDhanaSri commented 2 days ago

Hi @pratikwayal01,

I'm excited about the News Articles Category Prediction feature request! I have a strong background in Natural Language Processing and experience with text classification models, including BERT and other NLP techniques. I believe I can contribute effectively to the implementation and integration of this feature.

Could you please assign this issue to me?