Citation Recommendation: Approaches and Datasets
- URL: http://arxiv.org/abs/2002.06961v2
- Date: Thu, 14 May 2020 08:01:27 GMT
- Title: Citation Recommendation: Approaches and Datasets
- Authors: Michael F\"arber, Adam Jatowt
- Abstract summary: Citation recommendation describes the task of recommending citations for a given text.
In recent years, several approaches and evaluation data sets have been presented.
No literature survey has been conducted explicitly on citation recommendation.
- Score: 20.47628019708079
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Citation recommendation describes the task of recommending citations for a
given text. Due to the overload of published scientific works in recent years
on the one hand, and the need to cite the most appropriate publications when
writing scientific texts on the other hand, citation recommendation has emerged
as an important research topic. In recent years, several approaches and
evaluation data sets have been presented. However, to the best of our
knowledge, no literature survey has been conducted explicitly on citation
recommendation. In this article, we give a thorough introduction into automatic
citation recommendation research. We then present an overview of the approaches
and data sets for citation recommendation and identify differences and
commonalities using various dimensions. Last but not least, we shed light on
the evaluation methods, and outline general challenges in the evaluation and
how to meet them. We restrict ourselves to citation recommendation for
scientific publications, as this document type has been studied the most in
this area. However, many of the observations and discussions included in this
survey are also applicable to other types of text, such as news articles and
encyclopedic articles.
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