CITEWERTs: A System Combining Cite-Worthiness with Citation Recommendation
Buchtitel: Proceedings of the 40th European Conference on Information Retrieval (ECIR 2018)
Due to the vast amount of publications appearing inthe various scientific disciplines, there is a need for automatically recommending citations for text segments of scientific documents. Surprisingly, only few demonstrations of citation-based recommendersystems have been proposed so far. Moreover, existing solutions either do not consider the raw textual context or they recommend citations for predefined citation contexts or just for whole documents. In contrast to them, we propose a novel two-step architecture: First, given some input text, our system determines for each potential citation context, which is typically a sentence long, if it is actually "cite-worthy." When this is the case, secondly, our system recommends citations for that context. Given this architecture, in our demonstration we show how we can guide the user to only those sentences that deserve citations and how to present recommended citations for single sentences. In this way, we reduce the user's need to review too many sentences and recommendations.
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