Article thumbnail

Support for Location and Comprehension of User History in Collaborative Work

By Do Hyoung Kim


Users are being embraced as partners in developing computer services in many current computer supported cooperative work systems. Many web-based applications, including collaborative authoring tools like wikis, place users into collaborations with unknown and distant partners. Individual participants in such environments need to identify and understand others' contributions for collaboration to succeed and be efficient. One approach to supporting such understanding is to record user activity for later access. Issues with this approach include difficulties in locating activity of interest in large tasks and the history is often recorded at a system-activity level instead of at a human-activity level. To address these issues, this dissertation introduces CoActIVE, an application-independent history mechanism that clusters records of user activity and extracts keywords in an attempt to provide a human-level representation of history. CoActIVE is integrated in three different software applications to show its applicability and validity. Multiple visualization techniques based on this processing are compared in their ability to improve users' location and comprehension of the activity of others. The results show that filmstrip visualization and visual summarization of user activity show significant improvement over traditional list view interfaces. CoActIVE generates an interpretation of large-scale interaction history and provides the interpretation thorough a variety of visualizations that allow users to navigate the evolution of collaborative work. It supports branching history, with the understanding that asynchronous authoring and design tasks often involve the parallel development of alternatives. Additionally, CoActIVE has the potential to be integrated into a variety of applications with little adjustment for compatibility. Especially, the comparison of visualizations for locating and comprehending the work of others is unique

Topics: user history, history clustering, history visualization
Year: 2011
OAI identifier:

Suggested articles

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.