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1.
ABSTRACT

This article suggests that situations in which multiple research teams are convened under similar conditions present an opportunity to discover factors that lead to productive collaboration. It argues that social network analysis of research team outputs becomes more valuable when paired with data about research participant perceptions; and that any variables used as indicators of collaboration need to be calibrated using datasets from multiple studies with cross-team comparisons. The article provides an example of the kind of methodology needed to achieve this, describing a study with data from four research teams based at an Australian university campus, reporting their research performance over four years under conditions in which many variables were controlled and with results augmented by a survey of participant perceptions. Findings from the study indicate that there were exceptions to hypothesized associations between participant perceptions of collaboration and specific social network analysis measures over co-authorship data. The article suggests that, given the methodological challenges of studying research teams in the field, multiple datasets combining findings such as those in the present study are a path towards the development of indicators of productive higher education research collaboration.  相似文献   
2.
Majority opinions are often observed in the process of social interaction in online communities, but few studies have addressed this issue with empirical data. To identify an appropriate theoretical lens for explaining majority opinions in online environments, this study investigates the skewness statistic, which indicates how many “Likes” are skewed to major comments on a Facebook post; 3489 posts are gathered from the New York Times Facebook page for 100 days. Results show that time is not an influential factor for skewness increase, but the number of comments has a logarithmic relation to skewness increase. Regression models and Chow tests show that this relationship differs depending on topic contents, but majority opinions are significant in overall. These results suggest that the bandwagon effect due to social affordance can be a suitable mechanism for explaining majority opinion formation in an online environment and that majority opinions in online communities can be misperceived due to overestimation.  相似文献   
3.
[目的/意义] 公共图书馆地理空间布局影响着读者到馆方式和成本花费,进而影响读者对图书馆访问的体验和频次。[方法/过程] 基于出行链理论和场域理论,围绕公共图书馆地理空间布局,对读者访问公共图书馆的便利性进行了解析,分析了城市公共交通和生活设施分布和公共图书馆网络布局之间的动态关系和量化评价,利用ArcGIS对苏州城市公共图书馆布局进行了案例分析。[结果/结论] 提出建立与公共交通互动关系、接入图书馆馆外空间以及延伸到读者生活圈的策略,以提升公共图书馆地理空间布局便利性。  相似文献   
4.
Recommender Systems are currently highly relevant for helping users deal with the information overload they suffer from the large volume of data on the web, and automatically suggest the most appropriate items that meet users needs. However, in cases in which a user is new to Recommender System, the system cannot recommend items that are relevant to her/him because of lack of previous information about the user and/or the user-item rating history that helps to determine the users preferences. This problem is known as cold-start, which remains open because it does not have a final solution. Social networks have been employed as a good source of information to determine users preferences to mitigate the cold-start problem. This paper presents the results of a Systematic Literature Review on Collaborative Filtering-based Recommender System that uses social network data to mitigate the cold-start problem. This Systematic Literature Review compiled the papers published between 2011–2017, to select the most recent studies in the area. Each selected paper was evaluated and classified according to the depth which social networks used to mitigate the cold-start problem. The final results show that there are several publications that use the information of the social networks within the Recommender System; however, few research papers currently use this data to mitigate the cold-start problem.  相似文献   
5.
李慧  胡吉霞 《图书情报工作》2020,64(18):114-125
[目的/意义] 针对包含单一类型知识单元的知识网络难以全面反映学科知识结构的问题,提出一种从多维度进行知识网络结构融合的方法,为学科领域知识结构挖掘提供借鉴。[方法/过程] 利用LDA及TF-IDF方法抽取学科知识单元,然后运用语义相似度和关键词共现分析方法构建3个学科知识子网络:主题网络、关键词网络和实体网络,并采用空间节点传递对齐方法对齐子网络节点,接着设计基于图卷积操作的自编码模型对知识节点进行表示,最后通过计算余弦相似度重构学科知识网络。[结果/结论] 实验部分以人工智能领域为例,构建融合主题、关键词和实体的学科知识网络并展开分析,实验结果表明,本文所提方法能有效地揭示学科领域研究内容和知识结构,为学科知识发现与组织研究提供有益参考。  相似文献   
6.
ABSTRACT

This paper examines the social construction of ‘fashionability’ – namely, what is ‘desirable’ and ‘fashionable’ – with reference to the concept ‘cultural mediators’ that foregrounds agency, negotiation and the contested practices of market actors in cultural production. It zeroes in on the cultural mediators’ attitudes and positions in the two markets by drawing on 25 in-depth interviews with industry veterans. It shows that the mediators in South Korea and China increasingly occupy hybrid occupational roles and social positions across industries and sectors yet achieve limited success in countering the status quo of Western fashion through mediation. The analysis contributes to the literature with a categorisation of seven mediation practices that shape the valuation of fashion products (i.e. ‘fashionability’) in two ways. Empirically, this categorisation illuminates how cultural mediators make reference habitually to the broader social and cultural contexts to co-construct cultural-aesthetic objects. Theoretically, it advances a cultural-economic approach to the understanding of cultural mediation and challenges the reductionist viewpoint of actor–network theory through the notion of a matrix of cultural-economic agency.  相似文献   
7.
为提高船舶航迹预测精度,解决准确建模难度大和神经网络易陷入局部最优的问题,考虑实时获取目标船AIS数据较少的特点,提出一种基于支持向量机(support vector machine,SVM)的航迹预测模型。选择AIS数据中的航速、航向和船舶经纬度作为样本特征变量;采用小波阈值去噪的方法处理训练数据;采用差分进化(differential evolution,DE)算法对模型内部参数寻优以提高模型收敛速度和预测精度。选取天津港实船某段航迹的AIS数据,比较基于DE-SVM与基于BP神经网络的航迹预测模型的仿真结果。结果表明,基于DE-SVM的航迹预测模型具有更高的预测精度,简单、可行、高效,且耗时少。  相似文献   
8.
认知无线电是一种可用于有效缓解当前频谱资源紧张的技术,而频谱感知是认知无线电的前提。针对低信噪比情况下频谱感知性能差的问题,提出一种将信号高阶统计量、协方差矩阵特征值与神经网络相结合的合作频谱感知算法。该算法考虑到认知用户与授权用户的信道衰落情况,利用神经网络较强的多分类能力,将最大-最小特征值之比、平均-最小特征值之比以及高阶统计量作为特征参数,通过神经网络实现合作频谱感知。仿真结果表明,该算法不仅在低信噪比情况下较其他算法具有更高的频谱检测率,而且对频谱中信号的调制类型也有较高的识别率。  相似文献   
9.
ABSTRACT

As an important part of art and culture, ancient murals depict a variety of different artistic images, and these individual images have important research value. For research purposes, it is often important to first determine the type of objects represented in a painting. However, the mural painting environment makes datasets difficult to collect, and long-term exposure leads to underlying features that are not distinct, which makes this task challenging. This study proposes a convolutional neural network model based on the classic AlexNet network model and combines it with feature fusion to automatically classify ancient mural images. Due to the lack of large-scale mural datasets, the model first expands the dataset by applying image enhancement algorithms such as scaling, brightness conversion, noise addition, and flipping; then, it extracts the underlying features (such as fresco edges) shared by the first stage of a dual channel structure. Subsequently, a second-stage deep abstraction is conducted on the features extracted by the first stage using a two-channel network, each of which has a different structure. The obtained characteristics from both channels are merged, and a loss function is constructed to obtain the classification result. This approach improves the model's robustness and feature expression ability. The model achieves an accuracy of 84.24%, a recall rate of 84.15%, and an F1-measure of 84.13% when applied to a constructed mural image dataset. Compared with the AlexNet model and other improved convolutional neural network models, the proposed model improves each evaluation index by approximately 5%, verifying the rationality and effectiveness of the model for automatic mural image classification. The mural classification model proposed in this paper comprehensively considers the influences of network width and depth and can extract rich details from mural images from multiple local channels. An effective classification method could help researchers manage and protect mural images in an orderly fashion and quickly and effectively search for target images in a digital mural library based on a specified image category, aiding mural condition monitoring and restoration efforts as well as archaeological and art historical research.  相似文献   
10.
从国家和地方政策可以发现,体育产业集聚已成为中国体育产业发展的趋势。 然而体育产业集群作为一个复杂的网络主体,其发展与政府固然分不开,其内部组织结构、关系网络的优化才是集群优化的重点。研究创新构建了“网络特征—主体能力—企业绩效”理论模型,客观地揭示了变量之间的关系,并定量地证明了各变量间的相互作用。统计结果显示:体育产业集群的网络结构和网络关系对企业主体有直接的积极影响。体育企业的主体在网络规模与企业绩效、关系实力和企业绩效、关系质量和企业绩效之间具有明显的中介效应,在网络密度与企业绩效、网络开放性和企业绩效之间不具有中介效应。体育企业的主体获取和利用其他实体的资源并将其应用于生产过程将有助于提高企业绩效,对企业绩效的影响最大。研究对政府和体育企业层面分别提出了规范市场秩序、促进网络建设以及增进知识共享、提高网络质量等管理建议。  相似文献   
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