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Steven Xia
Researcher at Griffith University
Publications - 8
Citations - 536
Steven Xia is an academic researcher from Griffith University. The author has contributed to research in topics: Operational transformation & Application programming interface. The author has an hindex of 7, co-authored 8 publications receiving 525 citations. Previous affiliations of Steven Xia include Sybase.
Papers
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Journal ArticleDOI
Transparent adaptation of single-user applications for multi-user real-time collaboration
TL;DR: An innovative Transparent Adaptation approach and associated supporting techniques that can be used to convert existing and new single-user applications into collaborative ones, without changing the source code of the original application are reported.
Proceedings ArticleDOI
Leveraging single-user applications for multi-user collaboration: the coword approach
TL;DR: This approach has been applied to transparently convert MS Word into a real-time collaborative word processor, called CoWord, which supports multiple users to view and edit any objects in the same Word document at the same time over the Internet.
Proceedings ArticleDOI
Operational transformation for collaborative word processing
TL;DR: An extension of OT is reported for supporting a generic Update operation, in addition to Insert and Delete operations, for collaborative word processing, which is relevant not only to word processors but also to a range of interactive applications that can be modelled as editors.
Patent
Visualizing expressions for dynamic analytics
Steven Xia,Yean Fee Ho +1 more
TL;DR: In this article, a graphical user interface control is generated for each of one or more variables of an expression, and each of the variables is bound to the corresponding graphical interface control generated previously.
Patent
Fisheye-based presentation of information for mobile devices
TL;DR: In this paper, the user selects a focus row from the displayed data rows, a fisheye-based view of the selected focus row is presented, which provides the user with a focus-plus-context view of a large data list.