What are the common types of crawling strategies for deep web crawlers?

Common types of crawling strategies for deep web crawlers include:

1. Form-Based Crawling: This strategy involves submitting queries or filling out forms to access hidden content. The crawler identifies input fields, generates valid queries, and submits them to retrieve data.

   • Example: A crawler fills out a search form on an e-commerce site to access product listings that aren't indexed by search engines.

2. URL-Based Crawling: The crawler analyzes and follows dynamically generated URLs to access deep web pages. It may use patterns or rules to generate or predict URLs.

   • Example: A crawler detects URL structures like example.com/products?id=123 and iterates through ID values to fetch hidden pages.

3. Content-Based Crawling: The crawler prioritizes pages based on content relevance or freshness, often using machine learning or heuristics to identify valuable deep web content.

   • Example: A crawler focuses on fetching pages with recent updates or specific keywords from a news archive site.

4. Hybrid Crawling: Combines multiple strategies, such as form submission and URL pattern analysis, to maximize coverage of deep web resources.

   • Example: A crawler first submits a form to access a database and then follows dynamically generated links to fetch related pages.

For scalable and efficient deep web crawling, Tencent Cloud's Web+, Serverless Cloud Function (SCF), and TKE (Tencent Kubernetes Engine) can be used to deploy and manage crawlers, ensuring high performance and flexibility. Additionally, Tencent Cloud COS (Cloud Object Storage) can store large volumes of crawled data securely.