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Semantic Modelling of Citation Contexts for Context-aware Citation Recommendation


Semantic Modelling of Citation Contexts for Context-aware Citation Recommendation



Published: 2020 April

Buchtitel: Proceedings of the 42th European Conference on Information Retrieval (ECIR'20)
Seiten: 220--233
Verlag: Springer

Referierte Veröffentlichung

BibTeX

Kurzfassung
New research is being published at a rate, at which it is infeasible for many scholars to read and assess everything possibly relevant to their work. In pursuit of a remedy, efforts towards automated processing of publications, like semantic modelling of papers to facilitate their digital handling, and the development of information filtering systems, are an active area of research. In this paper, we investigate the benefits of semantically modelling citation contexts for the purpose of citation recommendation. For this, we develop semantic models of citation contexts based on entities and claim structures. To assess the effectiveness and conceptual soundness of our models, we perform a large offline evaluation on several data sets and furthermore conduct a user study. Our findings show that the models can outperform a non-semantic baseline model and do, indeed, capture the kind of information they’re conceptualized for.

Download: Media:SemCiteRec_ECIR2020.pdf



Forschungsgruppe

Web Science


Forschungsgebiet

Information Retrieval, Natürliche Sprachverarbeitung, Digitale Bibliotheken