Citation Recommendation
Citation recommendation is the task of determining the most relevant citations for a given piece of text in a specific domain. Due to the large number of documents published continuously, it is not easy to find the relevant documents for a topic. In this project, you will design and implement a deep learning-based model for citation recommendation in the domain of scientific publications.
Some of the related papers in this task are listed below:
- Michael Färber, Adam Jatowt, “Citation recommendation: approaches and datasets”, International Journal on Digital Libraries, 21:375–405, 2020, https://doi.org/10.1007/s00799-020-00288-2
- Zihan Huang, Charles Low, Mengqiu Teng, Hongyi Zhang, Daniel E. Ho, Mark S. Krass, Matthias Grabmaie, “Context-Aware Legal Citation Recommendation using Deep Learning”, ICAIL, p.79–88, 2021