This invention discloses a
deep web crawler method and
system based on multi-level
recursion, belonging to the field of computer and
artificial intelligence technology. The method includes data collection and preprocessing,
deep learning model selection and training, real-time monitoring and detection,
system integration and performance optimization. Data collection and preprocessing involves collecting data and cleaning and denoising it, as well as
feature extraction and transformation.
Deep learning model selection and training involves choosing different models or
hybrid models based on the
data type. Real-time monitoring and detection involves deploying the trained model to a real network environment and performing real-time monitoring and detection, monitoring the IP addresses of access requests, especially identifying a large number of requests from the same
IP address or a range of IP addresses, which suggests
web crawler activity. This invention can distinguish between normal users and web crawlers, helping websites and service providers effectively prevent malicious web crawlers and protect their data and resources from adverse effects.