一般绝对中心点网络选址问题

着重研究一般绝对中心点选址问题,考虑对象为网络图上所有的点.根据点与边的距离函数图形性质,给出了关于一般绝对中心点存在与如何寻找的定理,并利用所给定理解决了某居住区内消防站设立选址问题.     

求解奇异线性方程组的双逐次投影法

用双逐次投影迭代法来求解奇异线性方程组,当线性方程组的系数矩阵是对称半正定时,给出了不同情形时有关参量的选取以及相应的算法,并就收敛结果分别与雅可比迭代法和Gauss-Seidel迭代法进行了比较,数值结果表明,该方法对求解奇异线性方程组是很有效的.     

A Dual-Pointer guided transition system for end-to-end structured sentiment analysis with global graph reasoning

Structured sentiment analysis is a newly proposed task, which aims to summarize the overall sentiment and opinion status on given texts, i.e., the opinion expression, the sentiment polarity of the opinion, the holder of the opinion, and the target the opinion towards. In this work, we investigate a transition-based model for end-to-end structured sentiment analysis task. We design a transition architecture which supports the recognition of all the possible opinion quadruples in one shot. Based on the transition backbone, we then propose a Dual-Pointer module for more accurate term boundary detection. Besides, we further introduce a global graph reasoning mechanism, which helps to learn the global-level interactions between the overlapped quadruples. The high-order features are navigated into the transition system to enhance the final predictions. Extensive experimental results on five benchmarks demonstrate both the prominent efficacy and efficiency of our system. Our model outperforms all baselines in terms of all metrics, especially achieving a 10.5% point gain over the current best-performing system only detecting the holder-target-opinion triplets. Further analyses reveal that our framework is also effective in solving the overlapping structure and long-range dependency issues.     

新时期我国软科学研究前沿热点研究——基于软科学文献的知识图谱分析(2008—2018)

运用科学计量方法对软科学领域的六大核心期刊(2008—2018年)现状和研究热点进行分析。研究发现,目前我国软科学以国家创新驱动发展战略为主要研究方向,围绕区域创新体系及创新链的热点焦点问题和关键环节开展研究,同时,发现各个参与研究者之间合作紧密。研究运用描述性分析的方法,管窥我国软科学领域研究现状,并对未来发展做出展望,为我国软科学繁荣发展提供参考。     

Knowledge-guided multi-granularity GCN for ABSA

Aspect-based sentiment analysis aims to determine sentiment polarities toward specific aspect terms within the same sentence or document. Most recent studies adopted attention-based neural network models to implicitly connect aspect terms with context words. However, these studies were limited by insufficient interaction between aspect terms and opinion words, leading to poor performance on robustness test sets. In addition, we have found that robustness test sets create new sentences that interfere with the original information of a sentence, which often makes the text too long and leads to the problem of long-distance dependence. Simultaneously, these new sentences produce more non-target aspect terms, misleading the model because of the lack of relevant knowledge guidance. This study proposes a knowledge guided multi-granularity graph convolutional neural network (KMGCN) to solve these problems. The multi-granularity attention mechanism is designed to enhance the interaction between aspect terms and opinion words. To address the long-distance dependence, KMGCN uses a graph convolutional network that relies on a semantic map based on fine-tuning pre-trained models. In particular, KMGCN uses a mask mechanism guided by conceptual knowledge to encounter more aspect terms (including target and non-target aspect terms). Experiments are conducted on 12 SemEval-2014 variant benchmarking datasets, and the results demonstrated the effectiveness of the proposed framework.     

赋权完全图K_n中最短H圈与最短H通路

本文证明了赋权完全图Kn中关于最短H圈与最短H通路的两个定理,由此得到了它们的一个上确界.通过探讨最短H圈的有关性质,得到了关于最短H通路的对偶性结论,文末研究了它们之间的关系,使之更接近最优解.     

论潮筝快速催奏法原理及应用

传统潮筝催奏速度与弦诗乐催奏速度存在较大差距。潮筝快速催奏法"突破八度对称"弹奏模式,揉合潮乐的其他催奏形式,使潮筝的催奏速度达到弦诗乐演奏的要求,从而提高了潮筝在潮州音乐中的地位,并且丰富了潮州音乐的整体表现力。     

“与或图”与递归算法

介绍了用递归算法解决问题的基本方法以及与或图的定义,并通过两个实例介绍了借助"与或图"设计递归算法的方法。     

C_(5m)×C_(5n)图的邻点可区别的边染色

设G是阶数不小于3的简单连通图,G的k-正常边染色称为是邻点可区别的,如果对G任意相邻两顶点关联边的颜色集合不同,则k中最小者称为是G的邻点可区别的边色数.本文证明了C5m×C5n的邻点可区别的边色数是5.     

熵与周期的关系

设G为这样的有限图：它除含两个由一根线段连接的圈外不含其它圈,而且两个圈上的分支数相同．证明了连续自映射f．G→G的熵为零当且仅当存在k≤[（Edg（G）＋2End（G）＋11）／2]个不同的奇数n1,n2,…,nk使得Per（f）包含Ui=1^k uj=1^∞{n,2^f},其中Edg（G）、End（G）分别表示G的边数、端点数.