As it is cumbersome and expensive to acquire a huge amount of data for training neural dialog models, augmentation proposed effectively utilize existing samples. However, current techniques on the generation task mostly augment all cases in dataset without considering intrinsic attributes between different cases. We argue that not are beneficial task, suitable should obey following two attribut...

Purpose: The purpose of this article is to outline an algorithm for generating synthetic medical data in order augment small samples data. Methods: To achieve the research goal, methods such as: correlation analysis (to identify significant variables and relationships between them), MDR build logical chains data), regression model use generate data) were used. Results: A database heart failure ...

Provenance and other metadata are essential for determining ownership and trust. Nevertheless, no systematic approaches were introduced so far in the Linked Data publishing workflow to capture them. Defining such metadata remained independent of the rdf data generation and publishing. In most cases, metadata is manually defined by the data publishers (person-agents), rather than produced by the...