While there has been a trend in the last decades for publishing large-scale and highly-interconnected Knowledge Graphs (KGs), their users often get overwhelmed by task of understanding content as result size complexity. Data profiling approaches have proposed to summarize large KGs into concise meaningful representations, so that they can be better explored, processed, managed. Profiles based o...

Knowledge graph embedding (KGE) aims at learning powerful representations to benefit various artificial intelligence applications. Meanwhile, contrastive has been widely leveraged in as an effective mechanism enhance the discriminative capacity of learned representations. However, complex structures KG make it hard construct appropriate pairs. Only a few attempts have integrated strategies with...

Network structure learning algorithms have aided network discovery in fields such as bioinformatics, neuroscience, ecology and social science. However, challenges remain informative networks for related sets of tasks because the search space Bayesian structures is characterized by large basins approximately equivalent solutions. Multitask select a set that are near each other space, rather than...

social and political culture can be conceived as a trend consisting of ethical rules as its stractur, scientific thought as its process and dynamic knowledge of facts as its agenda elhical rules are intedecd to solve structural problems, scientific that is aimed at gaining knowledge corresponding with the facts, and the agenenda is not affaring truth but reliable and dynamic knowledge of the fa...

Background: Evaluation of multiple-choice questions is a strategic activity and the most effective tool in educational system and improvement. In this study, the quality of some indexes of multiple-choice exams in Babol Para Medical faculty was investigated on the basis of structure and knowledge level distribution in the first semesters of 2007 and 2012. Methods: The Milman checklist was used ...