| dc.description.abstract | Extracting valuable data from the vast resources of the web is crucial for business success.
Insights derived from analysing consumer behaviour, market trends, and operational
performance can inform strategic decision-making. However, traditional web scraping often
requires significant programming expertise and adapts poorly to website changes. While nocode tools exist, they can be costly and have limited capabilities.
The project addresses these challenges by developing a user-friendly, no-code web data
extraction with a focus on generalizing web scraping and data extraction process. The tool
aims to extract data from a wide range of websites while ensuring a meaningful, structured,
and analysable data output. The project will explore various methods of web scraping and
extraction based on the HTML tree parsing techniques. The tool utilizes a variety of scraping
frameworks such as Playwright and BeautifulSoup to achieve robust capabilities.
Additionally, the analysis module will integrate a Large Language Model (LLM) to further
enhance the usability of extracted data.
The research contributes to the field by offering a comprehensive, user-friendly tool that
supports the complete process of gather, extracting and analysing web data with no coding
involved. The tool will enable users across various fields to efficiently derive insights into
from web data, facilitating informed decision making and strategic planning. | en_US |
