This repository hosts a machine learning project that encompasses two key functionalities: a research papers recommendation system and subject area prediction. The goal of the project is to provide users with tailored recommendations based on their preferences and to predict the subject area of research papers.
Leveraging sentence transformers using sentence embedding with cosine similarity techniques to recommend research papers based on user preferences and similarities to other vectors.
Implementing a deep learning model to capture complex patterns implementing MLP to predict subject area of a paper.
Text Classification: Utilizing natural language processing techniques for classifying research papers into subject areas.
Prepare your research papers dataset with titles, abstracts, and corresponding subject areas. Text Classification:
Utilize the notebook to train models for predicting subject areas.
Research Papers Recommendation Recommending top K papers. The deep learning model improved recommendations, yielding an accuracy of 99%. Subject Area Prediction
License This project is licensed under the NOOR SAEED
Acknowledgments Mention any credits or acknowledgments for third-party tools, libraries, or resources used in the project.