An Automatic Approach for Extracting Process Knowledge from the Web

Abstract

Process knowledge, such as tasks involved in a process and the control flow and data flow among tasks, is critical for designing business processes. Such process knowledge enables service composition which integrates different services to implement business processes. In the current state of practice, business processes are primarily designed by experienced business analysts who have extensive process knowledge. It is challenging for novice business analysts and non-professional end-users to identify a complete set of services to orchestrate a well-defined business process due to the lack of process knowledge. In this paper, we propose an approach to extract process knowledge from existing commercial applications on the Web. Our approach uses a Web search engine to find websites containing process knowledge on the Internet. By analyzing the content and the structure of relevant websites, we extract the process knowledge from various websites and merge the process knowledge to generate an integrated ontology with rich process knowledge. We conduct a case study to compare our approach with a tool that extracts ontologies from textual sources. The result of the case study shows that our approach can extract process knowledge from online applications with higher precision and recall comparing to the ontology learning tool.