Crawl4AI Project: Data Collection Specification
Budget: $250 – $750 USD
I'm looking for a freelancer who can help create a detailed requirement document for the Crawl4AI project. This document should cover the collection scheme for gathering structured data from international news websites to support AI training.
Key Aspects to Cover:
- The primary focus is on collecting data for AI training.
- Targeting international news websites.
- Data types to be collected include textual content, images and multimedia.
Ideal Skills:
- Experience in technical writing, particularly in data collection for AI or machine learning projects.
- Familiarity with AI training processes and requirements.
- Understanding of data collection from news websites.
- Proficient in structuring complex information clearly and concisely.
Please provide examples of similar projects you've completed in your bid.
Requirement Document: Crawl4AI Data Collection Plan
1. Introduction
This requirement document aims to detail the Crawl4AI project’s data collection plan. The project is designed to collect structured data from multiple target news websites to support subsequent AI training and data analysis. This document covers the project’s objectives, functional requirements, technical specifications, data storage solutions, and other relevant details.
2. Project Objectives
Crawl4AI aims to efficiently, stably, and structurally collect data from the following four major Chinese news websites:
NetEase News (https://www.163.com/)
Tencent News (https://news.qq.com/)
Sina News (https://news.sina.com.cn/)
Sohu News (https://news.sohu.com/)
3. Target Websites
3.1 NetEase News
URL: https://www.163.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.2 Tencent News
URL: https://news.qq.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.3 Sina News
URL: https://news.sina.com.cn/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.4 Sohu News
URL: https://news.sohu.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
4. Functional Requirements
4.1 Data Collection
Category Classification: Based on the target website’s category structure, store articles under the following classifications:
News (e.g., Domestic, International)
Sports (e.g., NBA, Football)
Entertainment (e.g., Movies, Celebrities)
Article Archiving: Each article must be archived under its corresponding category to ensure organized data management and retrieval.
4.2 Data Fields
Each article must collect and store the following fields:
Title
Keywords
Description
Main Title (h1)
Article Content: Remove image URLs, retaining only textual content.
4.3 Data Format
File Format: Save each article as a .md (Markdown) file.
File Structure:
Header: Includes fields like title, keywords, description, etc.
Body: Contains only textual content without image URLs or HTML code.
HTML Code Cleaning:
Remove unnecessary tags and scripts, ensuring only content-related text data is retained.
4.4 Collection Frequency
Scheduled Tasks: Collect newly added articles daily.
Data Deduplication: Ensure previously collected data is not duplicated.
4.5 Dynamic IP Switching
IP Pool Management: Implement a dynamic IP pool, regularly switching collection IPs to avoid IP bans.
Proxy Mode: Support proxy mode with automatic IP detection and switching.
4.6 Data Storage
Storage Path: Save each website’s data under corresponding server folders based on categories.
Example Paths:
javascript
复制代码
/storage/news/163/
/storage/news/tencent/
/storage/news/sina/
/storage/news/sohu/
Category Directory Structure:
javascript
复制代码
/163/Sports/
/163/Entertainment/
/163/News/
5. Technical Requirements
5.1 Data Collection Technology
Dynamic Page Loading Support: Support scraping dynamically loaded pages (e.g., AJAX content). Recommended tools:
Puppeteer
Playwright
Data Parsing:
Python: Use BeautifulSoup
Node.js: Use Cheerio
5.2 IP Proxy
Proxy Pool Management: Support multiple proxy pool management tools, such as:
Bright Data
Self-built Dynamic Proxy Service
5.3 Data Storage and Cleaning
Markdown Data Saving Plan:
File Naming: Use article titles or unique IDs to prevent duplicates.
Content Formatting: Ensure clear formatting suitable for subsequent AI training or display purposes.
6. Additional Recommendations
6.1 Collection Logging and Monitoring
Log Recording: Save logs for each collection session, recording successfully and unsuccessfully collected articles.
Real-time Monitoring: Monitor collection frequency and IP status in real-time to ensure stable task operation.
6.2 Data Update Strategy
Incremental Updates: Provide daily incremental update interfaces to facilitate subsequent data processing and analysis.
Historical Version Saving: Save historical versions of articles with content modifications for comparison purposes.
6.3 Anti-Scraping Measures
Simulate User Behavior:
Add features to simulate user behavior, such as random access intervals and mouse scrolling.
User-Agent Updates:
Regularly update User-Agent strings to mimic real user access.
6.4 Scraper Performance Optimization
Distributed Scraping: Enhance task processing efficiency through distributed scraping (e.g., Scrapy Cluster).
Content Deduplication and Compression:
Deduplicate and compress collected content to reduce storage space usage.
7. Project Implementation Plan
7.1 Project Phases
Requirement Analysis and Confirmation
System Design
Development and Implementation
Testing and Optimization
Deployment and Launch
Maintenance and Updates
7.2 Timeline
Requirement Analysis and Confirmation: 1 week
System Design: 2 weeks
Development and Implementation: 4 weeks
Testing and Optimization: 2 weeks
Deployment and Launch: 1 week
Maintenance and Updates: Ongoing
8. Risks and Mitigation
8.1 Risk Identification
IP Bans
Target Website Structure Changes
Data Storage Anomalies
Insufficient Collection Frequency
8.2 Mitigation Strategies
IP Bans: Implement dynamic IP switching and use high-quality proxy pools.
Target Website Structure Changes: Regularly monitor website structures and promptly adjust scraping scripts.
Data Storage Anomalies: Adopt redundant storage and regular backup strategies.
Insufficient Collection Frequency: Optimize task scheduling and improve collection efficiency.
9. Conclusion
The Crawl4AI data collection plan aims to gather structured data from major Chinese news websites through efficient and stable technical methods. By clearly defining functional requirements and technical specifications, the project ensures smooth implementation and reliable data quality. The additional recommendations further enhance system stability and resilience against risks, laying a solid foundation for subsequent AI training and data analysis.
Key Aspects to Cover:
- The primary focus is on collecting data for AI training.
- Targeting international news websites.
- Data types to be collected include textual content, images and multimedia.
Ideal Skills:
- Experience in technical writing, particularly in data collection for AI or machine learning projects.
- Familiarity with AI training processes and requirements.
- Understanding of data collection from news websites.
- Proficient in structuring complex information clearly and concisely.
Please provide examples of similar projects you've completed in your bid.
Requirement Document: Crawl4AI Data Collection Plan
1. Introduction
This requirement document aims to detail the Crawl4AI project’s data collection plan. The project is designed to collect structured data from multiple target news websites to support subsequent AI training and data analysis. This document covers the project’s objectives, functional requirements, technical specifications, data storage solutions, and other relevant details.
2. Project Objectives
Crawl4AI aims to efficiently, stably, and structurally collect data from the following four major Chinese news websites:
NetEase News (https://www.163.com/)
Tencent News (https://news.qq.com/)
Sina News (https://news.sina.com.cn/)
Sohu News (https://news.sohu.com/)
3. Target Websites
3.1 NetEase News
URL: https://www.163.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.2 Tencent News
URL: https://news.qq.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.3 Sina News
URL: https://news.sina.com.cn/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
3.4 Sohu News
URL: https://news.sohu.com/
Sample Sections: Domestic, International, Sports, Entertainment, etc.
4. Functional Requirements
4.1 Data Collection
Category Classification: Based on the target website’s category structure, store articles under the following classifications:
News (e.g., Domestic, International)
Sports (e.g., NBA, Football)
Entertainment (e.g., Movies, Celebrities)
Article Archiving: Each article must be archived under its corresponding category to ensure organized data management and retrieval.
4.2 Data Fields
Each article must collect and store the following fields:
Title
Keywords
Description
Main Title (h1)
Article Content: Remove image URLs, retaining only textual content.
4.3 Data Format
File Format: Save each article as a .md (Markdown) file.
File Structure:
Header: Includes fields like title, keywords, description, etc.
Body: Contains only textual content without image URLs or HTML code.
HTML Code Cleaning:
Remove unnecessary tags and scripts, ensuring only content-related text data is retained.
4.4 Collection Frequency
Scheduled Tasks: Collect newly added articles daily.
Data Deduplication: Ensure previously collected data is not duplicated.
4.5 Dynamic IP Switching
IP Pool Management: Implement a dynamic IP pool, regularly switching collection IPs to avoid IP bans.
Proxy Mode: Support proxy mode with automatic IP detection and switching.
4.6 Data Storage
Storage Path: Save each website’s data under corresponding server folders based on categories.
Example Paths:
javascript
复制代码
/storage/news/163/
/storage/news/tencent/
/storage/news/sina/
/storage/news/sohu/
Category Directory Structure:
javascript
复制代码
/163/Sports/
/163/Entertainment/
/163/News/
5. Technical Requirements
5.1 Data Collection Technology
Dynamic Page Loading Support: Support scraping dynamically loaded pages (e.g., AJAX content). Recommended tools:
Puppeteer
Playwright
Data Parsing:
Python: Use BeautifulSoup
Node.js: Use Cheerio
5.2 IP Proxy
Proxy Pool Management: Support multiple proxy pool management tools, such as:
Bright Data
Self-built Dynamic Proxy Service
5.3 Data Storage and Cleaning
Markdown Data Saving Plan:
File Naming: Use article titles or unique IDs to prevent duplicates.
Content Formatting: Ensure clear formatting suitable for subsequent AI training or display purposes.
6. Additional Recommendations
6.1 Collection Logging and Monitoring
Log Recording: Save logs for each collection session, recording successfully and unsuccessfully collected articles.
Real-time Monitoring: Monitor collection frequency and IP status in real-time to ensure stable task operation.
6.2 Data Update Strategy
Incremental Updates: Provide daily incremental update interfaces to facilitate subsequent data processing and analysis.
Historical Version Saving: Save historical versions of articles with content modifications for comparison purposes.
6.3 Anti-Scraping Measures
Simulate User Behavior:
Add features to simulate user behavior, such as random access intervals and mouse scrolling.
User-Agent Updates:
Regularly update User-Agent strings to mimic real user access.
6.4 Scraper Performance Optimization
Distributed Scraping: Enhance task processing efficiency through distributed scraping (e.g., Scrapy Cluster).
Content Deduplication and Compression:
Deduplicate and compress collected content to reduce storage space usage.
7. Project Implementation Plan
7.1 Project Phases
Requirement Analysis and Confirmation
System Design
Development and Implementation
Testing and Optimization
Deployment and Launch
Maintenance and Updates
7.2 Timeline
Requirement Analysis and Confirmation: 1 week
System Design: 2 weeks
Development and Implementation: 4 weeks
Testing and Optimization: 2 weeks
Deployment and Launch: 1 week
Maintenance and Updates: Ongoing
8. Risks and Mitigation
8.1 Risk Identification
IP Bans
Target Website Structure Changes
Data Storage Anomalies
Insufficient Collection Frequency
8.2 Mitigation Strategies
IP Bans: Implement dynamic IP switching and use high-quality proxy pools.
Target Website Structure Changes: Regularly monitor website structures and promptly adjust scraping scripts.
Data Storage Anomalies: Adopt redundant storage and regular backup strategies.
Insufficient Collection Frequency: Optimize task scheduling and improve collection efficiency.
9. Conclusion
The Crawl4AI data collection plan aims to gather structured data from major Chinese news websites through efficient and stable technical methods. By clearly defining functional requirements and technical specifications, the project ensures smooth implementation and reliable data quality. The additional recommendations further enhance system stability and resilience against risks, laying a solid foundation for subsequent AI training and data analysis.