Joint Recognition of Names and Publications in Academic Homepages

Abstract

Academic homepages are an important source for learning researchers' profiles. Recognising person names and publications in academic homepages are two fundamental tasks for understanding the identities of the homepages and collaboration networks of the researchers. Existing studies have tackled person name recognition and publication recognition separately. We observe that these two tasks are correlated since person names and publications often co-occur. Further, there are strong position patterns for the occurrence of person names and publications. With these observations, we propose a novel deep learning model consisting of two main modules, an alternatingly updated memory module which exploits the knowledge and correlation from both tasks, and a position-aware memory module which captures the patterns of where in a homepage names and publications appear. Empirical results show that our proposed model outperforms the state-of-the-art publication recognition model by 3.64% in F1 score and outperforms the state-of-the-art person name recognition model by 2.06% in F1 score. Ablation studies and visualisation confirm the effectiveness of the proposed modules.