共查询到20条相似文献，搜索用时 31 毫秒
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《Information processing & management》2023,60(5):103418
Link prediction, which aims to predict future or missing links among nodes, is a crucial research problem in social network analysis. A unique few-shot challenge is link prediction on newly emerged link types without sufficient verification information in heterogeneous social networks, such as commodity recommendation on new categories. Most of current approaches for link prediction rely heavily on sufficient verified link samples, and almost ignore the shared knowledge between different link types. Hence, they tend to suffer from data scarcity in heterogeneous social networks and fail to handle newly emerged link types where has no sufficient verified link samples. To overcome this challenge, we propose a model based on meta-learning, called the meta-learning adaptation network (MLAN), which acquires transferable knowledge from historical link types to improve the prediction performance on newly emerged link types. MLAN consists of three main components: a subtask slicer, a meta migrator, and an adaptive predictor. The subtask slicer is responsible for generating community subtasks for the link prediction on historical link types. Subsequently, the meta migrator simultaneously completes multiple community subtasks from different link types to acquire transferable subtask-shared knowledge. Finally, the adaptive predictor employs the parameters of the meta migrator to fuse the subtask-shared knowledge from different community subtasks and learn the task-specific knowledge of newly emerged link types. Experimental results conducted on real-world social media datasets prove that our proposed MLAN outperforms state-of-the-art models in few-shot link prediction in heterogeneous social networks. 相似文献
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Steven Casper 《Research Policy》2007,36(4):438-455
Regional technology clusters are an important source of economic development, yet in biotechnology few successful clusters exist. Previous research links successful clusters to heightened innovation capacity achieved through the existence of social ties linking individuals across companies. Less understood are the mechanisms by which such networks emerge. The article uses social network analysis to examine the emergence of social networks linking senior managers employed in biotechnology firms in San Diego, California. Labor mobility within the region has forged a large network linking managers and firms, while ties linking managers of an early company, Hybritech, formed a network backbone anchoring growth in the region. 相似文献
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人居科学的超学科性质和特征 《科学学研究》2020,38(4):603-608
通过超学科概念的梳理，认为超学科是以模式3知识生产为基础的知识创新，涵盖了编码知识和默会知识，突破各单一学科固有知识边界和学科本身的藩篱。超学科没有范式，复杂性研究为其共同的学术硬核。在信息化网络社会，超学科注重学科与非学科知识的融合，注重不同层次间的整合，是多层次、多维度的知识集群。人居科学的超学科性质，在于人居本身的复杂性、多维性和多价值观。人居的概念几乎包含了人类社会生活的全部，不同学科的视线均可在“人居”这个研究对象上交叠。人类居住是人类从自然中分异出来，并独立于世的助推器，是人类思维形成、价值观形成的重要基础。人居科学是研究者、设计者、建设者、使用者等共同表述新愿望、共同达成从理论到方法的一致、共同产生新知识的过程。人居科学的超学科特征，是以复杂性研究为内核，以人居地域系统、社会信息网络系统为基础，以众多的知识集群和学科集群为主体，共同构成的开放的学术体系。 相似文献
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《Information processing & management》2020,57(4):102237
This paper analyses how the knowledge shared between employees and suppliers within a private enterprise social network affects process improvement. Data was collected from internal documents, and the internal and external enterprise social networks used by an international insurance company; the average cycle time for handling 8494 claims and 3240 messages posted on the internal and external social networks was analysed. Social network analysis techniques were combined with principal component analysis and structural equation modeling, and the results demonstrate that the knowledge shared within the internal and external social network can explain 35.10% of process improvement variability, while the knowledge shared within the internal social network explains 89.90% of external social network variability. The analysis also demonstrates that: (i) the knowledge shared among employees positively affects process improvement; (ii) the knowledge shared among suppliers negatively affects process improvement; and (iii) the knowledge shared among employees positively affects the knowledge shared among supply chain members. These findings have theoretical and practical implications. They extend the literature in the knowledge management and information management field by offering empirical evidence of how the knowledge shared through an enterprise social network affects business process improvement, using the objective data provided by Yammer. They also provide a strategic tool for managers that will allow them to better understand how they can use the enterprise social network for business processes improvement. 相似文献
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就引进型管理创新而言,获取已有创新知识,实现知识从组织外部向内部转移是关键.管理者所嵌入的社会网络通过提供广泛的多元化知识链接带来显著知识获取优势,促使管理者凭借网络影响力产生经济效益,从而成为管理创新知识获取的重要渠道.立足管理者个体社会网络视角,收集237家企业核心管理者的数据,通过多元回归分析,得出强连接优势显著,结构洞发挥实质作用,知识获取产生部分中介效应,社会网络、知识获取和管理创新引进水平之间整体影响关系成立等结论. 相似文献
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《Information processing & management》2023,60(2):103221
Disease spread control is a challenging task with growing importance in recent years. Infectious disease networks have been proven to be a helpful resource for controlling the epidemic by targeting a smaller population. However, the information on these networks is often imprecise, diffused, concealed, and misleading, making it challenging to obtain a complete set of real-world data, i.e., some links might be missing, which can be a risk to the widespread of the pandemic. The former studies on infectious disease networks ignore the influence of neighborhood missing links in the infectious disease network topology, thus massively targeting the irrelevant population, resulting in poor epidemic control performance. In this paper, to address such a problem, we study how a small portion of the population should be targeted with incomplete network information to effectively prevent the pandemic. We propose an algorithm, namely, the Neighborhood Relation Aware Network Dismantling Algorithm (NRAND), to efficiently address the infectious disease network’s dismantling problem. For comparison, four network dismantling strategies are employed in our experiments. An extensive empirical study of real-world networks suggests that the proposed algorithm NRAND’s dismantling performance is significantly greater than the state-of-the-art algorithms, indicating that NRAND can be a smarter option for dismantling real-world infectious disease networks. 相似文献
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对中国产业集群网论坛用户提问与回答的关系数据,建立了一个以自我中心,包括832个用户的知识传播网络模型。将该传播网络的传播模型与Watts通过Email方式建立的信息传递网络模型相比较。结合经典的传染模型和渗流模型及这两种信息传播网络的特点给出了相应的传播模型。不同的传播模型有不同的提高信息传播广度的方法：基于社会网络的信息传播不仅要提高信息传递者的激情而且要提高社会网的连通性,基于论坛回复关系的信息传播网络只需提高用户的回复激情就可扩大信息传播的广度。同时还给出了两种方式的难易程度,根据难易程度建议依据信息的不同性质在不同的网络中进行传播。 相似文献
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构建了移动社交网络基于情景化用户偏好的自适应适配信息服务系统模型,提出了移动社交网络的自适应服务发现方案。解决移动社交网络信息服务的发现与推送的延迟问题,实现高效的移动社交网络信息服务推送,对移动社交网络信息服务资源、知识资源进行科学管理。 相似文献
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《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
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新兴技术知识网络跨界融合的机理与实证研究 《科学学研究》2021,39(5):854-866
新兴技术跨界创新推动了知识网络的跨界融合演变。基于德温特专利数据库,以虚拟现实技术为研究对象,运用社会网络分析法,通过构建专利引文网络,研究新兴技术知识网络跨界融合的知识流动路径演化和网络态势。结果表明：新兴技术知识流动路径按照“单向路径-混向路径-双向路径”模式演化,核心企业和外围企业的不断增加拓宽了双向路径的发展空间;知识流动路径数量的激增和方向的分散导致企业和地区知识网络跨界融合的涌现,呈现出异质性知识增加、知识连接灵活、网络规模扩大的跨界融合特征;中心企业与中心地区通过“中心地区自引、非中心地区引中心地区”的知识流动偏好进一步强化跨界融合能力,体现出明显的先发优势。 相似文献
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《Information processing & management》2022,59(2):102873
Because the innovation level of enterprise clusters in various regions of China is generally low, this research is focused on the process of knowledge integration of regional innovation subjects. We research, explore and analyze the different connection states between nodes and their impact on the knowledge symbiosis or knowledge spillover ability of the entire innovation network, learn from the characteristics of neurons in the neural network and the information transmission model to investigate the connection between various nodes in innovation network. We then determine the knowledge association mechanism and transmission relationship, and then analyze the trigger conditions of fusion and the transformation model of innovative knowledge flow under this condition, laying the foundation for further theoretical or practical research. Second, we built a model of the knowledge transfer connection that will be used in the innovation process. and select a path of knowledge transfer. Based on the mechanism of multi-agent innovation, we analyzed the incentive relationship of knowledge transfer in the innovation process, constructed the principles of knowledge transfer, analyzed the mutual transfer relationship between different innovation nodes, and analyze the simulation innovation network through certain examples. The knowledge fusion process in China lays the foundation for the improvement of the overall collaborative innovation level of the regional multi-agent innovation network. From the overall structure of the article, this research analyzes the regional innovation network from a new perspective on the basis of domestic and foreign research in knowledge flow management and control technology, knowledge exchange under social networks, and neural network optimization algorithms. The process of knowledge symbiosis or knowledge spillover in the process of innovation, exploring the incentive relationship of knowledge transfer throughout the primary parts innovation process, optimizing the degree of connection or relationship between different main agents, optimizing the knowledge exchange relationship from one node in the innovation network to another and improving the collaborative innovation of the regional mesh lay a theoretical foundation for the level. 相似文献
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对国内外社会网络视角下的知识管理研究状况进行了系统归纳和总结,指出目前社会网络与知识管理的结合研究主要围绕社会网络视角下的企业知识活动形成机制、社会网络属性对知识管理中的知识活动着重研究社会网络、知识管理如何共同提升企业竞争力,社会网络、知识管理、竞争情报的交融以及企业知识网络等问题. 相似文献
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隐性知识是知识的核心,把隐性知识显性化出来也是创造知识的重要环节。社会性软件的出现,促进了知识的积累和创造。在社会性软件构建的环境下,从社会认知心理、马斯洛层次需要理论和社会网络弱链接等三方面分析社会性软件对隐性知识显性化的影响。 相似文献
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知识型企业核心员工离职时携带关键知识在组织间的同向迁移日益受到关注。基于社会资本视角对员工离职引发的知识由新雇主向原雇主反向迁移现象进行研究,是对目前关于核心员工离职引发关键知识迁移研究富有新意的拓展。认为作为社会资源载体的员工离职时,其社会网络嵌入方式发生变化,进而带来组织间联结的变化,并可能促使新,老雇主间结构洞的跨越及两者间关系网络的强化。对于员工离职引发的知识反向流动机制进行了初步分析,以期为企业优化核心员工离职过程中的知识管理机制,挖掘员工流动过程中的积极效应提供借鉴。 相似文献
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基于区域信息化建设的信息主体素质研究 总被引：1，自引：0，他引：1
基于区域信息化建设,阐述信息主体素质与信息化人才的关系,针对应用型本科高校具体情况,进行信息社会核心竞争力中的关键因素——信息主体素质研究。提出并构建知识素质、创新素质和能力素质,体现以信息社会适应性为核心的教学质量观和人才观,在教学实践中取得显著效果,学生的综合信息素质明显提高,更好地为区域信息化建设服务。 相似文献
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联盟网络会在不断演化中逐渐形成联系紧密的子网络,即派系。以派系为载体,企业间会相互学习,继而产生知识流动。本文结合派系和知识流动两大因素,从耦合角度出发,基于中国半导体行业的联盟数据,使用负二项回归模型,探索派系、知识流动及其耦合对联盟网络创新绩效的影响。研究发现:在不考虑联盟网络属性的情况下,派系内部关系数越多,企业创新能力越强;被引用、引用专利的次数越多,企业创新能力越强;派系作为调节变量,负向调节知识流动和企业创新能力。本研究有助于加强对联盟网络结构的了解,也为提高我国高新技术产业的企业创新能力提供借鉴。 相似文献