Zijing Tan

TL;DR: A novel generative adversarial learning based prediction method to obtain adversarially generated data for prediction model training by using long short-term memory units based recurrent neural network and attention mechanism is proposed.

TL;DR: Based on a repair framework by introducing a chase method, the repairs computing problem is discussed and the cost model for this repair framework is given, which can be used to evaluate the cost of each repair.

TL;DR: This paper provides a repair framework for inconsistent XML document with three basic update operations: node insertion, node deletion and value modification, and introduces the concept of labelled XML document, which is an extension to the traditional tree model of XML with a function to indicate the unreliable nodes.

TL;DR: A rich language for the definition of schema mappings is presented, which allow one to use various forms of document navigation and specify conditions on data values, and techniques to enforce non-key constraints on the canonical target instance are developed.