{"id":22845182,"url":"https://github.com/abz4375/recommendersystem","last_synced_at":"2026-04-13T03:10:24.962Z","repository":{"id":263744129,"uuid":"884284119","full_name":"abz4375/RecommenderSystem","owner":"abz4375","description":"A sophisticated recommender system that leverages web mining techniques to help users find hotels that match their preferences.","archived":false,"fork":false,"pushed_at":"2024-12-11T14:59:59.000Z","size":5156,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-06T09:47:49.042Z","etag":null,"topics":["cosine-similarity","css","html","javascript","pandas","python","scikit-learn","selenium","selenium-webdriver"],"latest_commit_sha":null,"homepage":"https://abz4375.github.io/RecommenderSystem/","language":"CSS","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/abz4375.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-11-06T13:30:42.000Z","updated_at":"2024-12-11T15:00:12.000Z","dependencies_parsed_at":null,"dependency_job_id":"fccbbcdc-0428-4a34-b098-ffcfe9c2b713","html_url":"https://github.com/abz4375/RecommenderSystem","commit_stats":null,"previous_names":["abz4375/recommendersystem"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abz4375%2FRecommenderSystem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abz4375%2FRecommenderSystem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abz4375%2FRecommenderSystem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abz4375%2FRecommenderSystem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abz4375","download_url":"https://codeload.github.com/abz4375/RecommenderSystem/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246421030,"owners_count":20774427,"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":["cosine-similarity","css","html","javascript","pandas","python","scikit-learn","selenium","selenium-webdriver"],"created_at":"2024-12-13T03:15:59.118Z","updated_at":"2026-04-13T03:10:24.933Z","avatar_url":"https://github.com/abz4375.png","language":"CSS","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Hotel Recommender System 🏨\n\n## Overview 🌟\nA sophisticated recommender system that leverages web mining techniques to help users find hotels that match their preferences. The system combines automated web scraping, real-time data processing, and machine learning to provide personalized hotel recommendations.\n\n## Features ✨\n- 🔄 Automated web scraping of hotel data from [Google Travel](https://www.google.com/travel/hotels)\n- ⚡ Real-time data processing capabilities\n- 🤖 Machine learning-based recommendation engine\n- 🖥️ Interactive user interface\n- 🎯 Personalized hotel recommendations\n\n## Key Hotel Features Analyzed 📋\nThe system analyzes the following amenities to provide tailored recommendations:\n```python\n- 🍳 Free breakfast\n- 📡 Free Wi-Fi\n- ❄️ Air conditioning\n- 🍽️ Restaurant\n- 🅿️ Free parking\n- 🛎️ Room service\n- 🏊 Pool\n- 👕 Full-service laundry\n- 💪 Fitness centre\n- 🍳 Kitchen\n- 🚌 Airport shuttle\n- 💆 Spa\n```\n\n## Technical Implementation 🛠️\nThe project demonstrates the integration of several key components:\n1. Web Mining - Automated data collection from hotel listings\n2. Data Processing - Real-time analysis of hotel features and amenities\n3. Machine Learning - Intelligent recommendation algorithm\n4. User Interface - Interactive platform for receiving user preferences\n\n## Project Structure 📁\n- Web scraping module for data collection\n- Data processing pipeline\n- Machine learning recommendation engine\n- User interface layer\n\n## Technology Stack 💻\n- [Python](https://www.python.org/)-based implementation\n- Machine Learning libraries ([scikit-learn](https://scikit-learn.org/stable/))\n- Web scraping tools\n- Data processing frameworks\n\n## Setup Instructions 🚀\n\n1. Create a virtual environment:\n```bash\npython -m venv venv\nsource venv/bin/activate  # On Unix/macOS\n# or\nvenv\\Scripts\\activate  # On Windows\n```\n\n2. Install required dependencies:\n```bash\npip install -r requirements.txt\n```\n\n## Usage 📝\n1. Start the recommender system:\n```bash\npython app.py\n```\n\n2. Access the web interface at `http://localhost:5000`\n\n---\n\nThis project provides a practical demonstration of how web mining techniques can be effectively applied to create a useful recommendation system that helps users find hotels matching their preferences. 🌐\n\n## Support 💡\nFor any questions or issues, please open an issue in the repository.\n\n        \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabz4375%2Frecommendersystem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabz4375%2Frecommendersystem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabz4375%2Frecommendersystem/lists"}