Automatic HTML form filling assistant
2022, vol.14 , no.4, pp. 79-88
Web application users fill data in web forms every day, and problem situations often arise due to various reasons (misunderstanding the requirements, entering wrong data or value outside a certain range, or applying some regular expression to a certain field, etc.). The paper proposes a hybrid approach to identify and classify different elements in a web document in an accurate and efficient way that optimizes and automates the process of data filling in web forms by users. Machine learning techniques, heuristics and dynamic analysis of HTML objects were used, and a script was developed to overcome difficulties in filling out forms. The advantage of the proposed script is that it can work with HTML documents regardless of the domain area, specificity and nature of their content, saving time in addition. The characteristics of the attributes and constraints of the input elements in web forms are extracted fully automatically and the generated messages to the users are synthesized based on a generalized structural rule.
web recognizing, web content extraction, HTML forms detection
Mariya Zhekova, Nedyalko Katrandzhiev. Automatic HTML form filling assistant. International Journal on Information Technologies and Security, vol.14 , no.4, 2022, pp. 79-88.