Auto-completion learning for XML.
SIGMOD/PODS '12: International Conference on Management of Data Scottsdale Arizona USA May, 2012(2012)
摘要
Editing an XML document manually is a complicated task. While many XML editors exist in the market, we argue that some important functionalities are missing in all of them. Our goal is to makes the editing task simpler and faster. We present ALEX (Auto-completion Learning Editor for XML), an editor that assists the users by providing intelligent auto-completion suggestions. These suggestions are adapted to the user needs, simply by feeding ALEX with a set of example XML documents to learn from. The suggestions are also guaranteed to be compliant with a given XML schema, possibly including integrity constraints. To fulfill this challenging goal, we rely on novel, theoretical foundations by us and others, which are combined here in a system for the first time.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络