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Prototypes and Models | Software Engineering | United States of America | Volume 13 Issue 4, April 2024
Next - Generation AI - Powered Web Scraping and Integration Platform for Seamless Transition to Modern Solutions
Naveen Koka
Abstract: The In an age characterized by rapid technological evolution, the landscape of software tools and applications is undergoing a profound transformation, driven by the proliferation of modern user interface (UI) designs and the rise of mobile - centric platforms. This paradigm shift promises increased accessibility, efficiency, and user engagement across various domains. However, amidst this wave of innovation, a significant portion of existing infrastructure remains entrenched in age - old systems, reluctant or unable to adapt to the changing technological landscape. Despite their antiquity, these systems often play critical roles within organizations, rendering them irreplaceable in the short term. This dichotomy presents a unique challenge: how to bridge the gap between legacy systems and modern tools, ensuring compatibility and longevity while embracing innovation. Finding solutions requires a delicate balance between preserving the functionality of established systems and integrating contemporary UI designs and mobile capabilities. Additionally, the modernization process must address scalability, security, and regulatory compliance considerations to meet the evolving needs of users and stakeholders. Through strategic planning, innovative development methodologies, and thoughtful integration of modern technologies, organizations can navigate this transition effectively. The abstract outlines the necessity of modernizing legacy systems, emphasizing the importance of embracing modern UI tools and mobile - centric approaches to unlock new opportunities, enhance user experiences, and drive sustainable growth in today's dynamic digital landscape. Utilizing state - of - the - art methodologies, our solution will harness the power of artificial intelligence to streamline the scraping process and ensure accurate extraction of HTML data. Through the incorporation of modern frameworks and technologies, we aspire to create an intuitive interface that enhances user experience and accessibility. By leveraging innovative approaches in data analysis and processing, our solution will enable the calculation and storage of embeddings for HTML content, thereby laying the foundation for advanced analytics and decision - making. Furthermore, the integration of machine learning models will empower the tool to identify patterns and anomalies, providing users with valuable insights and timely alerts. In summary, by embracing contemporary concepts and leveraging AI - driven technologies, our aim is to develop a sophisticated web scraping tool that not only addresses the specified requirements but also offers a rich and modern solution to the problem.
Keywords: LLM, Web Scrapping, Platform, AI
Edition: Volume 13 Issue 4, April 2024,
Pages: 194 - 197