본문 바로가기
  • Home

Adapted Sequential Pattern Mining Algorithms for Business Service Identification

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2009, 14(4), pp.109-121
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Jungwon Lee 1

1아주대학교

Accredited

ABSTRACT

The top-down method for SOA delivery is recommended as a best way to take advantage of SOA. The core step of SOA delivery is the step of service modeling including service analysis and design based on ontology. Most enterprises know that the top-down approach is the best but they are hesitant to employ it because it requires them to invest a great deal of time and money without it showing any immediate results, particularly because they use well-defined component based systems. In this paper, we propose a service identification method to use a well-defined components maximally as a bottom-up approach. We assume that user's inputs generates events on a GUI and the approximate business process can be obtained from concatenating the event paths. We first find the core GUIs which have many outgoing event calls and form event paths by concatenating the event calls between the GUIs. Next, we adapt sequential pattern mining algorithms to find the maximal frequent event paths. As an experiment, we obtained business services with various granularity by applying a cohesion metric to extracted frequent event paths.

Citation status

* References for papers published after 2022 are currently being built.