Kieu, Thanh Binh and Unanue, Inigo Jauregi and Pham, Bao Son and Phan, Xuan Hieu and Piccardi, Massimo (2020) Learning Neural Textual Representations for Citation Recommendation. In: The 25th International Conference on Pattern Recognition, Milan, Italy.
Full text not available from this repository.Abstract
With the rapid growth of the scientific literature, manually selecting appropriate citations for a paper is becoming increasingly challenging and time-consuming. While several approaches for automated citation recommendation have been proposed in the recent years, effective document representations for citation recommendation are still elusive to a large extent. For this reason, in this paper we propose a novel approach to citation recommendation which leverages a deep sequential representation of the documents (Sentence-BERT) cascaded with Siamese and triplet networks in a submodular scoring function. To the best of our knowledge, this is the first approach to combine deep representations and submodular selection for a task of citation recommendation. Experiments have been carried out using a popular benchmark dataset - the ACL Anthology Network corpus - and evaluated against baselines and a state-of-the-art approach using metrics such as the MRR and F1-at-k score. The results show that the proposed approach has been able to outperform all the compared approaches in every measured metric.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Information Technology (IT) ISI/Scopus indexed conference |
| Divisions: | Faculty of Information Technology (FIT) |
| Depositing User: | A/Prof. Xuan Hieu Phan |
| Date Deposited: | 10 Dec 2020 02:41 |
| Last Modified: | 10 Dec 2020 02:41 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/4216 |
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