方面级情感分析旨在识别文本中针对特定方面的情感倾向,然而现有研究仍面临多重挑战:基于BERT的方面级情感分析研究存在语义过拟合、低层级语义利用不足的问题;自注意力机制存在局部信息丢失的问题;多编码层和多粒度语义的结构存在信息...方面级情感分析旨在识别文本中针对特定方面的情感倾向,然而现有研究仍面临多重挑战:基于BERT的方面级情感分析研究存在语义过拟合、低层级语义利用不足的问题;自注意力机制存在局部信息丢失的问题;多编码层和多粒度语义的结构存在信息冗余问题。为此,提出一种融合BERT编码层的多粒度语义方面级情感分析模型(multi-granular semantic aspect-based sentiment analysis model with fusion of BERT encoding layers,MSBEL)。具体地,引入金字塔注意力机制,利用各个编码层的语义特征,并结合低层编码器以降低过拟合;通过多尺度门控卷积增强模型处理局部信息丢失的能力;使用余弦注意力突出与方面词相关的情感特征,从而减少信息冗余。t-SNE的可视化分析表明,MSBEL的情感表示聚类效果优于BERT。此外,在多个基准数据集上将本文模型与主流模型的性能进行了对比,结果显示:与LCF-BERT相比,本文模型在5个数据集上的F1分别提升了1.53%、3.94%、1.39%、6.68%、5.97%;与SenticGCN相比,本文模型的F1平均提升0.94%,最大提升2.12%;与ABSA-DeBERTa相比,本文模型的F1平均提升1.16%,最大提升4.20%,验证了本文模型在方面级情感分析任务上的有效性和优越性。展开更多
An opportunistic maintenance model is presented for a continuously deteriorating series system with economical de-pendence. The system consists of two kinds of units, which are respectively subjected to the deteriorat...An opportunistic maintenance model is presented for a continuously deteriorating series system with economical de-pendence. The system consists of two kinds of units, which are respectively subjected to the deterioration failure described by Gamma process and the random failure described by Poisson process. A two-level opportunistic policy defined by three decision parameters is proposed to coordinate the different maintenance actions and minimize the long-run maintenance cost rate of the system. A computable expression of the average cost rate is established by using the renewal property of the stochastic process of the maintained system state. The optimal values of three deci- sion parameters are derived by an iteration approach based on the characteristic of Gamma process. The behavior of the proposed policy is illustrated through a numerical experiment. Comparative study with the widely used corrective maintenance policy demonstrates the advantage of the proposed opportunistic maintenance method in significantly reducing the maintenance cost. Simultane- ously, the applicable area of this opportunistic model is discussed by the sensitivity analysis of the set-up cost and random failure rate.展开更多
文摘方面级情感分析旨在识别文本中针对特定方面的情感倾向,然而现有研究仍面临多重挑战:基于BERT的方面级情感分析研究存在语义过拟合、低层级语义利用不足的问题;自注意力机制存在局部信息丢失的问题;多编码层和多粒度语义的结构存在信息冗余问题。为此,提出一种融合BERT编码层的多粒度语义方面级情感分析模型(multi-granular semantic aspect-based sentiment analysis model with fusion of BERT encoding layers,MSBEL)。具体地,引入金字塔注意力机制,利用各个编码层的语义特征,并结合低层编码器以降低过拟合;通过多尺度门控卷积增强模型处理局部信息丢失的能力;使用余弦注意力突出与方面词相关的情感特征,从而减少信息冗余。t-SNE的可视化分析表明,MSBEL的情感表示聚类效果优于BERT。此外,在多个基准数据集上将本文模型与主流模型的性能进行了对比,结果显示:与LCF-BERT相比,本文模型在5个数据集上的F1分别提升了1.53%、3.94%、1.39%、6.68%、5.97%;与SenticGCN相比,本文模型的F1平均提升0.94%,最大提升2.12%;与ABSA-DeBERTa相比,本文模型的F1平均提升1.16%,最大提升4.20%,验证了本文模型在方面级情感分析任务上的有效性和优越性。
基金supported by the National Natural Science Foundation of China(6090400271201166)
文摘An opportunistic maintenance model is presented for a continuously deteriorating series system with economical de-pendence. The system consists of two kinds of units, which are respectively subjected to the deterioration failure described by Gamma process and the random failure described by Poisson process. A two-level opportunistic policy defined by three decision parameters is proposed to coordinate the different maintenance actions and minimize the long-run maintenance cost rate of the system. A computable expression of the average cost rate is established by using the renewal property of the stochastic process of the maintained system state. The optimal values of three deci- sion parameters are derived by an iteration approach based on the characteristic of Gamma process. The behavior of the proposed policy is illustrated through a numerical experiment. Comparative study with the widely used corrective maintenance policy demonstrates the advantage of the proposed opportunistic maintenance method in significantly reducing the maintenance cost. Simultane- ously, the applicable area of this opportunistic model is discussed by the sensitivity analysis of the set-up cost and random failure rate.
