Wang, R., Yan, Y., Wang, J., Jia, Y., Zhang, Y., Zhang, W., & Wang, X. (2018). AceKG: A Large-scale Knowledge Graph for Academic Data Mining. Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Abstract Most existing knowledge graphs (KGs) in academic domains suffer from problems of insufficient multi-relational information, name ambiguity and improper data format for large-scale machine processing. In this paper, we present AceKG, a new large-scale KG in academic domain. AceKG not only provides clean academic information, but also offers a large-scale benchmark dataset for researchers to conduct challenging data mining projects including link prediction, community detection and scholar classification. Specifically, AceKG describes 3.13 billion triples of academic facts based on a consistent ontology, including necessary properties of papers, authors, fields of study, venues and institutes, as well as the relations among them. To enrich the...
Postagens
Brack A., Hoppe A., Ewerth R. (2021) Citation Recommendation for Research Papers via Knowledge Graphs. In: Berget G., Hall M.M., Brenn D., Kumpulainen S. (eds) Linking Theory and Practice of Digital Libraries. TPDL 2021. Lecture Notes in Computer Science, vol 12866. Springer, Cham. https://doi.org/10.1007/978-3-030-86324-1_20 Abstract Citation recommendation for research papers is a valuable task that can help researchers improve the quality of their work by suggesting relevant related work. Current approaches for this task rely primarily on the text of the papers and the citation network. ** O SPECTER seria o estado da arte no sentido da proposta com melhores resultados ** In this paper, we propose to exploit an additional source of information, namely research knowledge graphs (KGs) that interlink research papers based on mentioned scientific concepts. ** O KG é composto de conceitos e documentos ** Our experimental results demonstrate that the combination of ...
Sadeghi A., Lange C., Vidal ME., Auer S. (2017) Integration of Scholarly Communication Metadata Using Knowledge Graphs . In: Kamps J., Tsakonas G., Manolopoulos Y., Iliadis L., Karydis I. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2017. Lecture Notes in Computer Science, vol 10450. Springer, Cham. https://doi.org/10.1007/978-3-319-67008-9_26 Abstract Important questions about the scientific community, e.g., what authors are the experts in a certain field, or are actively engaged in international collaborations , can be answered using publicly available datasets. However, data required to answer such questions is often scattered over multiple isolated datasets. Recently, the Knowledge Graph (KG) concept has been identified as a means for interweaving heterogeneous datasets and enhancing answer completeness and soundness. We present a pipeline for creating high quality knowledge graphs that comprise data collected from multiple isolated st...