Zobrazeno 1 - 10
of 170
pro vyhledávání: '"Sujian Li"'
Publikováno v:
Applied Sciences, Vol 13, Iss 5, p 3035 (2023)
The iron and steel industry is a pillar industry of the national economy in many countries and is also a source of high energy consumption and pollution gas emissions. In addition to the economic aspect, there have been increasing concerns over how t
Externí odkaz:
https://doaj.org/article/f595fc11b15a4808bd9bb241fde9cc54
Publikováno v:
PLoS ONE, Vol 13, Iss 7, p e0197933 (2018)
Deep learning techniques, e.g., Convolutional Neural Networks (CNNs), have been explosively applied to the research in the fields of information retrieval and natural language processing. However, few research efforts have addressed semantic indexing
Externí odkaz:
https://doaj.org/article/644a2746255c4b7c87dbd40a4bf31621
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2015 (2015)
Public transit providers are facing continuous pressure to improve service quality and reduce operating costs. Bus driver scheduling is among the most studied problems in this area. Based on this, flexible and powerful optimization algorithms have th
Externí odkaz:
https://doaj.org/article/9ef05a64e3cc49c3ad5dbfd7e2877e8b
Publikováno v:
Journal of Industrial and Production Engineering. 40:246-270
Publikováno v:
Bioengineered. 13:10552-10563
Circular RNAs (circRNAs) are involved in the carcinogenesis of lung cancer. Human MYC gene is highly expressed in melanoma, multiple myeloma, and nasopharyngeal carcinoma. We aimed to investigate the role of circMYC in small cell lung cancer (SCLC).
Unsupervised extractive summarization aims to extract salient sentences from a document as the summary without labeled data. Recent literatures mostly research how to leverage sentence similarity to rank sentences in the order of salience. However, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::45e3c52dfcab1d24f58272771faea425
http://arxiv.org/abs/2302.12490
http://arxiv.org/abs/2302.12490
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 30:1-11
Automatically solving math word problems is a critical task in the field of natural language processing. Recent models have reached their performance bottleneck and require more high-quality data for training. We propose a novel data augmentation met
Autor:
Xiangyang Li, Bo Chen, Huifeng Guo, Jingjie Li, Chenxu Zhu, Xiang Long, Sujian Li, Yichao Wang, Wei Guo, Longxia Mao, Jinxing Liu, Zhenhua Dong, Ruiming Tang
Scoring a large number of candidates precisely in several milliseconds is vital for industrial pre-ranking systems. Existing pre-ranking systems primarily adopt the \textbf{two-tower} model since the ``user-item decoupling architecture'' paradigm is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16602abcc021f02303a7e9cf30337634
http://arxiv.org/abs/2210.09890
http://arxiv.org/abs/2210.09890
Text style transfer (TST) without parallel data has achieved some practical success. However, most of the existing unsupervised text style transfer methods suffer from (i) requiring massive amounts of non-parallel data to guide transferring different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5de3f2aa96bd68a2a801e6c00cf0b3ed
http://arxiv.org/abs/2205.12475
http://arxiv.org/abs/2205.12475
Autor:
Yishan Zhang, Sujian Li
Publikováno v:
SSRN Electronic Journal.