Abstract
In recent years, new digital technologies are being used to support the navigation and the analysis of scientific publications, justified by the increasing number of articles published every year. For this reason, experts make use of on-line systems to browse thousands of articles in search of relevant information. In this paper, we present a new method that automatically assigns meanings to references on the basis of the citation text through a Natural Language Processing pipeline and a slightly-supervised clustering process. The resulting network of semantically-linked articles allows an informed exploration of the research panorama through semantic paths. The proposed approach has been validated using the ACL Anthology Dataset containing several thousands of papers related to the Computational Linguistics field. A manual evaluation on the extracted citation meanings carried to very high levels of accuracy. Finally, a freely-available web-based application has been developed and published on-line.
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Notes
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nsubj, csubj, nmod, advcl, dobj.
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The Porter Stemmer has been adopted.
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We excluded from the evaluation the 10th cluster related-to since it included the remaining citations having a very broad scope.
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Since we did not have a complete labeled corpus with positive and negative examples, we could not compute standard Precision/Recall/F-measures.
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Both documentation and source code of the pipeline, as well as the complete set of citation snippets per category and the graph, are available at https://github.com/rogerferrod/citexp.
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Ferrod, R., Schifanella, C., Di Caro, L., Cataldi, M. (2019). Disclosing Citation Meanings for Augmented Research Retrieval and Exploration. In: Hitzler, P., et al. The Semantic Web. ESWC 2019. Lecture Notes in Computer Science(), vol 11503. Springer, Cham. https://doi.org/10.1007/978-3-030-21348-0_7
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