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Recommender system and search engine for scholarly articles/research papers using Doc2Vec

Home Page: https://deviantpadam.pythonanywhere.com/

Python 11.85% CSS 60.44% JavaScript 5.40% HTML 22.31%
python flask recommender-system recommendation-engine doc2vec nlp spacy scholarly-articles research-paper

researchpaperscholarlyarticlesrecsystem's Introduction

recommender_system_research_papers_or_scholarly_articles_doc2vec

Recommender system for Scholarly Articles Dataset available at https://www.kaggle.com/neelshah18/arxivdataset and text file for topics explanation is copied from https://arxiv.org/archive/cs


Site is live on http://deviantpadam.pythonanywhere.com/
Instructions to run the flask app -
  1. Install git
  2. Open cmd/terminal
  3. Clone this repository using git clone https://github.com/DeviantPadam/rec_system.git or download the zip file.
  4. Install required dependencies from requirement.txt using pip install package_name or conda install -c
  5. Open cmd/terminal and set current directory to repository directory using cd repository_path
  6. Execute export FLASK_APP=recommender.py(linux) or set FLASK_APP=recommender.py (windows)
  7. Then execute flask run
  8. Click on the development link to see the flask app

researchpaperscholarlyarticlesrecsystem's People

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