{"id":16520196,"url":"https://github.com/khadkarajesh/recommender-system","last_synced_at":"2025-07-02T01:32:02.326Z","repository":{"id":44611794,"uuid":"453142309","full_name":"khadkarajesh/recommender-system","owner":"khadkarajesh","description":"Implicit Event Based Recommendation Engine for Ecommerce","archived":false,"fork":false,"pushed_at":"2022-02-05T19:14:14.000Z","size":17719,"stargazers_count":4,"open_issues_count":1,"forks_count":1,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-08T17:12:26.092Z","etag":null,"topics":["ecommerce","flask","flask-restful","heroku","implicit","lightfm","postgresql","python","recommender-system","sklearn","streamlit","surprise"],"latest_commit_sha":null,"homepage":"https://share.streamlit.io/khadkarajesh/recommender-system","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/khadkarajesh.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-01-28T16:40:13.000Z","updated_at":"2024-07-18T21:43:07.000Z","dependencies_parsed_at":"2022-09-03T05:01:55.670Z","dependency_job_id":null,"html_url":"https://github.com/khadkarajesh/recommender-system","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/khadkarajesh/recommender-system","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khadkarajesh%2Frecommender-system","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khadkarajesh%2Frecommender-system/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khadkarajesh%2Frecommender-system/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khadkarajesh%2Frecommender-system/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/khadkarajesh","download_url":"https://codeload.github.com/khadkarajesh/recommender-system/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/khadkarajesh%2Frecommender-system/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263059824,"owners_count":23407416,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ecommerce","flask","flask-restful","heroku","implicit","lightfm","postgresql","python","recommender-system","sklearn","streamlit","surprise"],"created_at":"2024-10-11T16:50:00.818Z","updated_at":"2025-07-02T01:32:02.302Z","avatar_url":"https://github.com/khadkarajesh.png","language":"Python","readme":"# Recommender System\n\nIt is ecommerce based recommendation engine built on operational data one of the ecommerce application. It uses the hybrid approach to recommend products. Hybrid approach combines both attribute of user, items to solve the problem of cold start and data sparsity. User attributes: Age, Gender and Items attributes: Price, Brand, Category has been considered along with interaction's purchase, click, wishlist to built model\n\n## Used Technologies\n\n* Flask\n* Python\n* Streamlit\n* Postgresql\n\n## Steps to Run Application\n\n1. [Install Dependencies](#install-dependencies)\n2. [Run API](#run-api)\n3. [Run Frontend](#run-frontend)\n\n### Install Dependencies\n\n1. Create a virtual environment with python3\n   ```shell\n   python3 -m virtualenv venv\n   ```\n2. Activate the virtual environment:\n   ```shell\n   cd venv\n   source /bin/activate\n   ```\n2. Install dependencies\n   ```shell\n   pip install -r requirements.txt\n   ```\n\n### Run API\n\n1. Configure the database Create database and add .env file in ```api/.env```. template of ```.env``` is as follows:\n   ```shell\n   DATABASE_NAME =\n   DATABASE_PORT =\n   USER_NAME =\n   USER_PASSWORD =\n   ```\n2. Navigate to root of the project\n3. Set environment variables\n   ```bash\n   export FLASK_APP=app:create_app\n   export APP_SETTINGS=\"api.config.DevelopmentConfig\"\n   ```\n4. Run Flask\n   ```bash\n   flask run\n   ```\n\n### Run Frontend\n\n1. Run streamlit application as:\n\n```bash\n   streamlit run streamlit_app.py\n```\n\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhadkarajesh%2Frecommender-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkhadkarajesh%2Frecommender-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhadkarajesh%2Frecommender-system/lists"}