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1.
In Part I of this paper we presented a formal procedure for determining the various state structures associated with any given digital network with the dimension of state vector equal to the number of dynamic elements in the network. For noncanonic networks, it is sometimes possible to find state structures with state vectors of reduced and even lowest dimension. Such a state structure is defined to be reduced state structure except for the case where state vector dimension is the lowest possible (the associated state structure is termed minimal). A graph-theoretic procedure for determing the existence of conditions under which a state structure can be simplified is outlined in this part of the paper. 相似文献
2.
Human collaborative relationship inference is a meaningful task for online social networks and is called link prediction in network science. Real-world networks contain multiple types of interacting components and can be modeled naturally as heterogeneous information networks (HINs). The current link prediction algorithms in HINs fail to effectively extract training samples from snapshots of HINs; moreover, they underutilise the differences between nodes and between meta-paths. Therefore, we propose a meta-circuit machine (MCM) that can learn and fuse node and meta-path features efficiently, and we use these features to inference the collaborative relationships in question-and-answer and bibliographic networks. We first utilise meta-circuit random walks to obtain training samples in which the basic idea is to perform biased meta-path random walks on the input and target network successively and then connect them. Then, a meta-circuit recurrent neural network (mcRNN) is designed for link prediction, which represents each node and meta-path by a dense vector and leverages an RNN to fuse the features of node sequences. Experiments on two real-world networks demonstrate the effectiveness of our framework. This study promotes the investigation of potential evolutionary mechanisms for collaborative relationships and offers practical guidance for designing more effective recommendation systems for online social networks. 相似文献
3.
This paper presents a formal precedure for determining the state-space representations of any digital network consisting of adders, multipliers, and delays. Such representations are called state structures whenever the state variables are exclusively identified to the appropriately chosen internal node variables of the network. In general, the state structures corresponding to a given network are not unique. In Part I of the paper we present techniques of obtaining the various state structures where the associated state vectors have dimensions equal to the number of dynamic elements (in our case delays) in the network. In Part II we shall treat the subject of lowering the dimension of such state-space representations. 相似文献
4.
Disheng Tang Wenbo Du Louis Shekhtman Yijie Wang Shlomo Havlin Xianbin Cao Gang Yan 《国家科学评论(英文版)》2020,7(5):929
Links in most real networks often change over time. Such temporality of links encodes the ordering and causality of interactions between nodes and has a profound effect on network dynamics and function. Empirical evidence has shown that the temporal nature of links in many real-world networks is not random. Nonetheless, it is challenging to predict temporal link patterns while considering the entanglement between topological and temporal link patterns. Here, we propose an entropy-rate-based framework, based on combined topological–temporal regularities, for quantifying the predictability of any temporal network. We apply our framework on various model networks, demonstrating that it indeed captures the intrinsic topological–temporal regularities whereas previous methods considered only temporal aspects. We also apply our framework on 18 real networks of different types and determine their predictability. Interestingly, we find that, for most real temporal networks, despite the greater complexity of predictability brought by the increase in dimension, the combined topological–temporal predictability is higher than the temporal predictability. Our results demonstrate the necessity for incorporating both temporal and topological aspects of networks in order to improve predictions of dynamical processes. 相似文献
5.
《Information processing & management》2022,59(3):102917
Nowadays, signed network has become an important research topic because it can reflect more complex relationships in reality than traditional network, especially in social networks. However, most signed network methods that achieve excellent performance through structure information learning always neglect neutral links, which have unique information in social networks. At the same time, previous approach for neutral links cannot utilize the graph structure information, which has been proved to be useful in node embedding field. Thus, in this paper, we proposed the Signed Graph Convolutional Network with Neutral Links (NL-SGCN) to address the structure information learning problem of neutral links in signed network, which shed new insight on signed network embedding. In NL-SGCN, we learn two representations for each node in each layer from both inner character and outward attitude aspects and propagate their information by balance theory. Among these three types of links, information of neutral links will be limited propagated by the learned coefficient matrix. To verify the performance of the proposed model, we choose several classical datasets in this field to perform empirical experiment. The experimental result shows that NL-SGCN significantly outperforms the existing state-of-the-art baseline methods for link prediction in signed network with neutral links, which supports the efficacy of structure information learning in neutral links. 相似文献
6.
《Information processing & management》2022,59(2):102869
User-created automation applets to connect IoT devices and applications have become popular and widely available. Exploring those applets enables us to grasp the patterns of how users are utilizing and maximizing the power of connection by themselves, which can deliver practical implications for IoT service design. This study builds an IoT application network with the data of the IFTTT(if this then that) platform which is the most popular platform for self-automation of IoT services. The trigger-action relationships of the IFTTT applets currently activated are collected and used to construct an IoT application network whose nodes are IoT service channels, and links represent their connections. The constructed IoT network is then embedded by the node2vec technique, an algorithmic framework for representational learning of nodes in networks. Clustering the embedded nodes produces the four clusters of IoT usage patterns: Smart Home, Activity Tracking, Information Digest, and Lifelogging & Sharing. We also predict the IoT application network using node2vec-based link prediction with several machine learning classifiers to identify promising connections between IoT applications. Feasible service scenarios are then generated from predicted links between IoT applications. The findings and the proposed approach can offer IoT service providers practical implications for enhancing user experiences and developing new services. 相似文献
7.
村落空间网络是以农村居民点为节点、线性设施为依托、节点相互作用而构成的复杂网络。开展村落空间网络及其节点中心性研究能够理清节点在网络中的关键位置与影响范围,为农村居民点规划建设、整体网络结构优化提供理论借鉴。本文以重庆市江津区燕坝村为例,运用复杂网络理论与方法构建村落空间网络,进而辨析网络中心点及其辐射强度与辐射范围,厘定出农村居民点体系优化重组模式。结果表明：① 村落空间网络具有典型的非均衡层次结构、小世界特征与无标度特性,网络整体的联系程度较低;② 依据中心点的辐射能力划分其等级,形成Ⅰ级中心点、Ⅱ级中心点和Ⅲ级节点共同作用的网络节点体系;③ 基于此,从“整体-局部-个体”3个影响层次,构建了中心村（Ⅰ级中心点）扩散型、基层村（Ⅱ级中心点）增长型、散居农村居民点（Ⅲ级节点）挖潜型3类优化重组模式。 相似文献
8.
《Information processing & management》2016,52(2):217-257
Transductive classification is a useful way to classify texts when labeled training examples are insufficient. Several algorithms to perform transductive classification considering text collections represented in a vector space model have been proposed. However, the use of these algorithms is unfeasible in practical applications due to the independence assumption among instances or terms and the drawbacks of these algorithms. Network-based algorithms come up to avoid the drawbacks of the algorithms based on vector space model and to improve transductive classification. Networks are mostly used for label propagation, in which some labeled objects propagate their labels to other objects through the network connections. Bipartite networks are useful to represent text collections as networks and perform label propagation. The generation of this type of network avoids requirements such as collections with hyperlinks or citations, computation of similarities among all texts in the collection, as well as the setup of a number of parameters. In a bipartite heterogeneous network, objects correspond to documents and terms, and the connections are given by the occurrences of terms in documents. The label propagation is performed from documents to terms and then from terms to documents iteratively. Nevertheless, instead of using terms just as means of label propagation, in this article we propose the use of the bipartite network structure to define the relevance scores of terms for classes through an optimization process and then propagate these relevance scores to define labels for unlabeled documents. The new document labels are used to redefine the relevance scores of terms which consequently redefine the labels of unlabeled documents in an iterative process. We demonstrated that the proposed approach surpasses the algorithms for transductive classification based on vector space model or networks. Moreover, we demonstrated that the proposed algorithm effectively makes use of unlabeled documents to improve classification and it is faster than other transductive algorithms. 相似文献
9.
In this paper, the fixed-time synchronization between two delayed complex networks with hybrid couplings is investigated. The internal delay, transmission coupling delay and self-feedback coupling delay are all included in the network model. By introducing and proving a new and important differential equality, and utilizing periodically semi-intermittent control, some fixed-time synchronization criteria are derived in which the settling time function is bounded for any initial values. It is shown that the control rate, network size and node dimension heavily influence the estimating for the upper bound of the convergence time of synchronization state. Finally, numerical simulations are performed to show the feasibility and effectiveness of the control methodology by comparing with the corresponding finite-time synchronization problem. 相似文献
10.
本研究利用“一带一路”沿线国家跨国PCT专利合作申请信息构建5个技术领域科技合作网络,采用社会网络分析方法从网络可视图、网络整体结构指标和网络中心性指标三方面进行对比分析。研究结果表明,一方面,各技术领域科技合作网络中节点国家的合作广度和合作强度均表现出明显的不均衡性,网络均呈现网络规模较大、网络密度低、平均距离短的特征,网络中核心国家基本上都是经济较发达的国家;另一方面,5个技术领域科技合作网络中的大节点及高频合作国家对有所区别,网络分属不同类型,网络中核心国家的分布与排序亦有所不同。上述研究结果对沿线各国制定适合的科技合作政策、开展各具特色的跨国科技合作有一定的借鉴意义。 相似文献
11.
社会资本对科学家科研绩效的影响研究 《科学学研究》2022,40(2):288-296
本文从结构维、认知维和关系维出发,研究科研合作网络中的社会资本对科学家科研绩效的影响。我们从web of science上收集了化学领域26.74万篇论文,基于这些论文作者合作数据构建了科学家合作网络,并从上述三个方面对其中的社会资本进行了测度。研究结果显示,认知维社会资本和关系维社会资本在一定程度上对科研绩效具有显著的促进作用,而结构维社会资本对科研人员的科研绩效具有显著的非线性关系。本文为建立积极有效的科研合作网络,高效利用合作网络中的社会资本为科学家更好地开展科研活动提供了一定借鉴。 相似文献
12.
Studying information flow between node clusters can be conceptualised as an important challenge for the knowledge management research and practice community. We are confronted with issues related to establishing links between nodes and/or clusters during the process of information flow and search transfer in large distributed networks. In the case of missing socio-technical links, social networks can be instrumental in supporting the communities of practice interested in sharing and transferring knowledge across informal links. A comprehensive review of methodology for detecting missing links is provided. The proportion of common neighbours was selected as best practice to elicit missing links from a large health insurance data set. Weights were based on geographical arrangements of providers and the dollar value of transactions. The core network was elicited based on statistical thresholds. Suspicious, possibly fraudulent, behaviour is highlighted based on social network measures of the core. Our findings are supported by a health insurance industry expert panel. 相似文献
13.
基于改进KNN的文本分类方法 总被引：8，自引：0，他引：8
本文针对VSM (向量空间模型)中KNN (K最近邻算法)在文本处理环境下的不足,根据SOM (自组织映射神经网络)理论、特征选取和模式聚合理论,提出了一种改进的KNN文本分类方法。应用特征选取和模式聚合理论以降低特征空间维数。传统的VSM模型各维相同的权重并不适应于文本处理的环境,本文提出应用SOM神经网络进行VSM模型各维权重的计算。结合两种改进,有效地降低了向量空间的维数,提高了文本分类的精度和速度。 相似文献
14.
本文提出一种新的H/S(Harris/SIFT)特征点提取算法,在此基础上根据三角形相似性原理,引入基线三角形组及复数空间,使传统的被动搜索三角形变为主动构造三角形,并利用多模板实现图像匹配。实验表明该匹配算法在图像存在旋转、尺度变化等情况下具有良好的应用性能。 相似文献
15.
16.
在分析了无线传感器网络应用和特性的基础上,论述了无线传感器网络中的网络体系结构、节点体系结构、与距离有关的节点能量计算模型、带有Flag标志和长期睡眠机制的状态转换模型,并给出了几种流行的无线传感器网络路由算法及其特点,对无线传感器网络的应用和研究有着深远的意义。 相似文献
17.
本文首先提出一种改进的X^2统计量，以此衡量词条对文本分类的贡献。然后根据模式聚合理论，将对各文本类分类贡献比例相近似的词条聚合为一个特征，建立出文本集的特征向量空间模型。此方法有效地降低了文本特征向量空间的维数。最后使用决策树进行分类，从而既保证了分类精度又获得了决策树易于抽取可理解的分类规则的优势。 相似文献
18.
This paper aims to further our understanding of how embeddedness affects the research output and impact of scientists. The analysis uses an extensive panel data that allows an analysis of within person variation over time. It explores the simultaneous effects of different dimensions of network embeddedness over time at individual level. These include the establishment of direct ties, the strengths of these ties, as well as the density, structural holes, centrality, and cross-disciplinary links. Results suggest that the network dynamics behind the generation of quality output contrasts dramatically with that of quantity. We find that the relational dimension of scientists matters for quality, but not for output, while cognitive dimensions have the opposite effect, helping output, while being indifferent toward impact. The structural dimension of the network is the only area where there is some degree of convergence between output quantity and quality; here, we find a prevalence for the role of brokerage over cohesion. It concludes by discussing implications for both network research and science policy. 相似文献
19.
Jan van den Ende 《Research Policy》2003,32(8):1501-1518
This paper focuses on governance modes for service development of mobile telephone networks (GSM, Wireless Application Protocol (WAP), GPRS, UMTS). ‘Services’ refer to services containing information. The paper shows that the phase of the life cycle of the network and the service affects the choice of governance mode of new service development projects. Governance modes include internal development by the telecom operator, several forms of collaboration between telecom operator and service firm, and only providing a network by the telecom operator to the service firm, which then develops and provides its services (external). In this paper a model is developed for the governance mode of service development in different phases of the life cycles of the mobile network and service, based on the degrees of uncertainty and urgency involved in the network and service development processes. Four cases are presented of service development projects for mobile telecom networks. These cases indicate that the number of redesigns and the level of communication costs in collaboration projects indeed depend on the degree of urgency and uncertainty involved in these projects, which are in turn affected by the life cycle of the network and service. 相似文献