Abstract
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 language | English |
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Title of host publication | Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC-2016) |
Place of Publication | Portorož, Slovenia |
Publisher | European Language Resources Association (ELRA) |
Pages | 1737-1742 |
Number of pages | 6 |
ISBN (Electronic) | 978-2-9517408-9-1 |
ISBN (Print) | 978-2-9517408-9-1 |
Publication status | Published - May 2016 |
Event | 10th edition of the Language Resources and Evaluation Conference - Portorož , Slovenia Duration: 23 May 2016 → 28 May 2016 http://lrec2016.lrec-conf.org/en/ http://www.lrec-conf.org/proceedings/lrec2016/index.html |
Conference
Conference | 10th edition of the Language Resources and Evaluation Conference |
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Abbreviated title | LREC 2016 |
Country/Territory | Slovenia |
City | Portorož |
Period | 23/05/16 → 28/05/16 |
Internet address |