BiMuF: a bi-directional recommender system with multi-semantic filter for online recruitment-Reference-Cited by-同舟云学术

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BiMuF: a bi-directional recommender system with multi-semantic filter for online recruitment

Published:2023-10-17 Issue: Volume: Page:
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Lai Pei-Yuan,Yang Zhe-Rui,Dai Qing-Yun,Liao De-Zhang,Wang Chang-Dong

Funder

NSFC

Guangdong Province Key Laboratory of Computational Science at the Sun Yat-sen University

Support Scheme of Guangzhou for Leading Talents in Innovation and Entrepreneurship

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10115-023-01997-1.pdf

Reference53 articles.

1. He J, Liu R, Zhuang F, Lin F, Niu C, He Q(2018) A general cross-domain recommendation framework via Bayesian neural network. In: ICDM, pp 1001– 1006

2. Chen T, Wong RC-W ( 2019) Session-based recommendation with local invariance. In: ICDM, pp 994– 999

3. Chen X, Chen H, Xu H, Zhang Y, Cao Y, Qin Z, Zha H ( 2019)Personalized fashion recommendation with visual explanations based on multimodal attention network: towards visually explainable recommendation. In: SIGIR, pp 765– 774

4. Cheng L, Shi Y, Li L, Yu H, Wang X, Yan Z (2023) KLECA: knowledge-level-evolution and category-aware personalized knowledge recommendation. Knowl Inf Syst 65(3):1045–1065

5. Zhao W, Wang B, Yang M, Ye J, Zhao Z, Chen X, Shen Y (2020) Leveraging long and short-term information in content-aware movie recommendation via adversarial training. IEEE Trans Cybern 50(11):4680–4693

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