HierClasSArt: Knowledge-Aware Hierarchical Classification of Scholarly Articles

摘要: A huge number of scholarly articles published every day in different domains makes it hard for the experts to organize and stay updated with new research a particular domain. This study gives an overview approach, HierClasSArt, knowledge aware hierarchical classification mathematics into predefined taxonomy. The method uses combination neural networks Knowledge Graphs better document representation along meta-data information. position paper further discusses open problems about incorporation evolving hierarchies pipeline. Mathematics domain has been used as use-case.