Applying Core Scientific Concepts to Context-Based Citation Recommendation

Daniel Duma, Maria Liakata, Amanda Clare, James Ravenscroft, Ewan Klein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

The task of recommending relevant scientific literature for a draft academic paper has recently received significant interest. In our effort to ease the discovery of scientific literature and augment scientific writing, we aim to improve the relevance of results based on a shallow semantic analysis of the source document and the potential documents to recommend. We investigate the utility of automatic argumentative and rhetorical annotation of documents for this purpose. Specifically, we integrate automatic Core Scientific Concepts (CoreSC) classification into a prototype context-based citation recommendation system and investigate its usefulness to the task. We frame citation recommendation as an information retrieval task and we use the categories of the annotation schemes to apply different weights to the similarity formula. Our results show interesting and consistent correlations between the type of citation and the type of sentence containing the relevant information.
Original languageEnglish
Title of host publicationProceedings of the Tenth International Conference on Language Resources and Evaluation (LREC-2016)
Place of PublicationPortorož, Slovenia
PublisherEuropean Language Resources Association (ELRA)
Number of pages6
ISBN (Electronic)978-2-9517408-9-1
ISBN (Print)978-2-9517408-9-1
Publication statusPublished - May 2016
Event10th edition of the Language Resources and Evaluation Conference - Portorož , Slovenia
Duration: 23 May 201628 May 2016


Conference10th edition of the Language Resources and Evaluation Conference
Abbreviated titleLREC 2016
Internet address


Dive into the research topics of 'Applying Core Scientific Concepts to Context-Based Citation Recommendation'. Together they form a unique fingerprint.

Cite this