An intelligent framework for auto-filling web forms from different web applications

Shaohua Wang, Ying Zou, Iman Keivanloo, Bipin Upahyaya, Joanna Ng

Research output: Contribution to journalArticlepeer-review

Abstract

End-users compose ad-hoc business processes by integrating web applications to conduct online tasks. Generally, end-users have to enter information into web forms of web applications, and often repetitively type the same information into applications. It could be a tedious job for end-users to fill in web forms with identical information. To save end-users from repetitive typing and increase composition productivity, it is critical to propagate and pre-fill user inputs to web applications. In this paper, we propose an intelligent auto-filling framework collecting and propagating user inputs across web applications, identifying user usage patterns and contexts. The empirical results show that our framework, on average, achieves a precision of 74.5% and a recall of 58% on pre-filling web forms, and a precision of 82.25% and a recall of 68.4% on suggesting values to end-users if the end-users edit the initial pre-filled values.

Original languageEnglish (US)
Pages (from-to)16-30
Number of pages15
JournalInternational Journal of Business Process Integration and Management
Volume8
Issue number1
DOIs
StatePublished - 2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Strategy and Management
  • Management Science and Operations Research

Keywords

  • Business process integration
  • Clustering
  • Context-aware
  • Usage patterns
  • Web form auto-filling

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