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High-Pass Text Filtering for Citation Matching

Open publications are increasing at such a rapid pace that it is almost impossible for researchers to keep up with them. Even in terms of computational complexity, the data are becoming bigger and bigger, so there is a great need to provide new and faster algorithms for mining scientific articles. One such important mining task is finding citation links between the literature, which can assist researchers looking into the literature, finding dependencies between publications, and so on. In this paper, we introduce a greedy citation matching algorithm, that works with plain unstructured text and mines citations from papers regardless of the format in which the citations are presented. This research is supported by the European Commission under projects OpenAIRE2020 (643410) and Human Brain Project (720270).

Foufoulas, Y., Stamatogiannakis, L., Dimitropoulos, H., & Ioannidis, Y. (2017, September). High-pass text filtering for citation matching. In International Conference on Theory and Practice of Digital Libraries (pp. 355-366). Springer, Cham.
Published at
TPDL 2017
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