TY  - CONF
ID  - SisLab3639
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3639/
A1  - Kieu, Thanh Binh
A1  - Pham, Bao Son
A1  - Phan, Xuan Hieu
A1  - Piccardi, Massimo
Y1  - 2019/10/11/
N2  - Choosing appropriate references for a given topic is an important, yet challenging task. The pool of potential candidates is typically very large, in the order of tens of thousands, and growing by the day. For this reason, this paper proposes an approach for automatically providing a reference list for a given abstract. The approach is based on an original submodular inference function which balances relevance, coverage and diversity in the reference list. Experiments are carried out using an ACL corpus as a source for the references and evaluated in terms of precision-recall, MAP and MRR. The results show the remarkable comparative performance of the proposed approach.
TI  - A Submodular Approach for Reference Recommendation
M2  - Hanoi, Vietnam
AV  - none
T2  - The 16th International Conference of the Pacific Association for Computational Linguistics (PACLING 2019)
ER  -