INFORMATION RETRIEVAL FROM DEEP WEB

The deep web, which refers to the parts of the World Wide Web that are not indexed by standard search engines, contains a vast amount of valuable and unstructured information that is not easily accessible to the general public. In this paper, we propose a new system architecture that integrates web crawling, advanced query processing, machine learning, and natural language processing techniques to improve the efficiency of information retrieval from the deep web. The proposed system is designed to be efficient and accurate, providing real-time analysis of the retrieved data. The use of advanced techniques in each module ensures accurate retrieval and analysis of information from the deep web. The proposed architecture will contribute to the advancement of information retrieval from the deep web and have a significant impact on various domains, including academia, business, and national security.