Liu, Ling

Associated Organization(s)
Organizational Unit
ArchiveSpace Name Record

Publication Search Results

Now showing 1 - 2 of 2
  • Item
    Distributed Workflow Restructuring: An Experimental Study
    (Georgia Institute of Technology, 2002) Ruiz, Duncan Dubugras ; Liu, Ling ; Pu, Calton
    Workflow systems have been one of the enabling technologies for automation of business processes in corporate enterprises. Many modern production workflows need to incorporate deadline control throughout the workflow management system. However, the increasing volume and diversity of digital information available online and the unpredictable amount of network delays or server failures have led to a growing problem that conventional workflow management systems do not have, namely how to reorganize existing workflow activities in order to meet deadlines in the presence of unexpected delays. We refer to this problem as the workflow-restructuring problem. This paper describes the notation and issues of workflow restructuring, and discusses a set of workflow activity restructuring operators. We illustrate the inherent semantics of these restructuring operators using the Transactional Activity Model (TAM). The paper contains two main contributions. First, we study the environmental instabilities (e.g., resource shortages and network delays) that cause workflows to perform sub-optimally and how workflow restructuring can address this problem. Second, we evaluate the effectiveness of workflow-restructuring operators through simulation. Our initial experiments demonstrate that run-time workflow restructuring can improve response time significantly for unstable environments.
  • Item
    Omini: A Fully Automated Object Extraction System for the World Wide Web
    (Georgia Institute of Technology, 2000) Buttler, David John ; Liu, Ling ; Pu, Calton
    This paper presents a fully automated object extraction system - Omini.A distinct feature of Omini is the suite of algorithms and the automatically learned information extraction rules for discovering and extracting objects from dynamic Web pages or static Web pages that contain multiple object instances. We evaluated the system using more than 2,000 Web pages over 40 sites. It achieves 100% precision (returns only correct objects) and excellent recall (between 93% and 98%, with very few significant objects left out). The object boundary identification algorithms are fast, about 0.1 second per page with a simple optimization.