期刊文献+
共找到3篇文章
< 1 >
每页显示 20 50 100
Research Progress in Biological Control of Soft Rot of Amorphophallus konjac
1
作者 Lisha NIU Tongshu DAI +6 位作者 Zhenliang CAO boxuan jia Bo HUANG Lijuan DENG Shuanglin YANG Zhen REN Yu ZHONG 《Asian Agricultural Research》 2023年第5期41-43,共3页
In this paper,the main control methods of soft rot of Amorphophallus konjac are reviewed,with a focus on the current research status of using plant growth promoting rhizobacteria for biological control of soft rot of ... In this paper,the main control methods of soft rot of Amorphophallus konjac are reviewed,with a focus on the current research status of using plant growth promoting rhizobacteria for biological control of soft rot of A.konjac,and future research directions are looked forward to. 展开更多
关键词 Amorphophallus konjac Soft rot Plant growth promoting rhizobacteria Induced resistance
下载PDF
PSHCAR: A Position-Irrelevant Scene-Aware Human Complex Activities Recognizing Algorithm on Mobile Phones
2
作者 boxuan jia Jinbao Li Hui Xu 《国际计算机前沿大会会议论文集》 2018年第1期15-15,共1页
下载PDF
Natural Language Inference Using Evidence from Knowledge Graphs
3
作者 boxuan jia Hui Xu Maosheng Guo 《国际计算机前沿大会会议论文集》 2021年第2期3-15,共13页
Knowledge plays an essential role in inference,but is less explored by previous works in the Natural Language Inference(NLI)task.Although traditional neural models obtained impressive performance on standard benchmark... Knowledge plays an essential role in inference,but is less explored by previous works in the Natural Language Inference(NLI)task.Although traditional neural models obtained impressive performance on standard benchmarks,they often encounter performance degradation when being applied to knowledge-intensive domains like medicine and science.To address this problem and further fill the knowledge gap,we present a simple Evidence-Based Inference Model(EBIM)to integrate clues collected from knowledge graphs as evidence for inference.To effectively incorporate the knowledge,we propose an efficient approach to retrieve paths in knowledge graphs as clues and then prune them to avoid involving too much irrelevant noise.In addition,we design a specialized CNN-based encoder according to the structure of clues to better model them.Experiments show that the proposed encoder outperforms strong baselines,and our EBIM model outperforms other knowledge-based approaches on the SciTail benchmark and establishes a new state-of-the-art performance on the MedNLI dataset. 展开更多
关键词 Knowledge graphs Natural language processing Natural Language Inference Neural networks
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部