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111.
《International Journal of Information Management》2016,36(1):1-8
Social media is growing rapidly. Providing both risks and opportunities for organizations as it does. The social strategy cone is developed for evaluating social media strategies. This framework comprises of seven key elements of social media strategies as based on a systematic literature review and case studies. The results of 21 interviews have contributed to the construction of the social media strategy cone for analyzing social media strategies. Three levels of maturity of social media strategy are proposed: initiation, diffusion and maturity. Initiation includes the key elements: ‘target audience’ and ‘channel choice’ while all case organizations studied payed attention to these elements. Diffusion includes the elements: ‘goals’, ‘resources’ and ‘policies’. Maturity adds the elements of ‘monitoring’ and ‘content activities’. Only 3 of the 9 organizations studied are in this phase of maturity. Although, theory suggests the importance of the element of ‘monitoring’ our research shows the need for more attention in practice. 相似文献
112.
Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms 总被引:1,自引:0,他引:1
Sung-Kwun Oh 《Journal of The Franklin Institute》2006,343(2):125-136
In this paper, we introduce a new architecture of genetic algorithms (GA)-based self-organizing polynomial neural networks (SOPNN) and discuss a comprehensive design methodology. Let us recall that the design of the “conventional” PNNs uses an extended group method of data handling (GMDH) and exploits polynomials (such as linear, quadratic, and modified quadratic functions) as well as considers a fixed number of input nodes (as being selected in advance by a network designer) at polynomial neurons (or nodes) located in each layer. The proposed GA-based SOPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional PNNs. The design procedure applied in the construction of each layer of a PNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomial, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the network. To evaluate the performance of the GA-based SOPNN, the model is experimented with using chaotic time series data. A comparative analysis reveals that the proposed GA-based SOPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature. 相似文献
113.
114.
无线传感器网络节点有着严格的能量限制,目前已有的许多路由协议假定了节点知道网络的全局信息或者让节点根据路由表进行路由。这些方式均会使网络产生较多的通信负荷,增大能量开销。结合多源单汇路由的特点,本文提出了几种局部路由算法。该算法中,节点仅根据目标节点与邻居节点的地理位置、剩余能量等信息,决定下一跳节点,最终建立到达目的节点的路径。本文首次引入了带约束后跳发射的思想,并将这种后跳发射与已有的算法相结合得到新的后跳路由算法。计算机仿真实验表明,在有数据融合的网络中,带约束的后跳-为难度路由算法使得网络的生存时间最长,较其余算法增加了网络11%和14%的工作周期数。最后又将局部路由算法进行合理改进,得到最小化平均为难度的算法,应用于无数据融合的网络中,效果很好。 相似文献
115.
知识选择(KS)是一种全新的方法,其过程由三个滤波器实现:(1)辨识过程,即根据查询的组合属性选择知识项。(2)自适应过程,即为滤波而使用相关的背景适应知识。(3)预测过程,即提前几步预测未来的查询。本文提出了用神经网络求解KS问题的方法以及KS在计算机安全领域的应用方法。 相似文献
116.
使用网络分析方法,揭示了创新网络-技术联系和交融-技术协作,会出现一种技术联结体、技术整体和技术共同体的现象,基于对这种现象的分析,从共同体建设4个方面,提供了强化技术联系联结、力图驾驭这种技术共同体的着力点和方法,以提高创新成功率和创新网络素质。 相似文献
117.
118.
刘智慧 《湖南师范大学社会科学学报》2011,40(5):119-122
词汇是构成语言的三大要素之一,它在承载着语音的内容同时又体现着语法的功能。词汇作为一个开放的体系,是语言中最敏感、最富于变化的部分。网络的出现催生了大量的网络词语。我们的研究表明,英汉网络词语主要通过合成、缩略、转义和生造法构成,体现了两种语言的共性,反映了网络语言的简洁、新颖和不稳定性。 相似文献
119.
避免构造Lyapunov函数的困难,运用广义Dahlquist数方法研究了一类神经网络模型平衡点的存在唯一性和指数稳定性,在没有假设激活函数具有可微性、有界性的条件下,得出新的判据。 相似文献
120.
《Journal of Informetrics》2019,13(2):485-499
With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics, and bibliometrics establish quantified analysis methods and measurements for evaluating scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to the paper, since this metric is widely utilized in the evaluation of scientific publications and moreover, it serves as the basis for many other metrics such as h-index. In this paper, we propose a novel method for predicting long-term citations of a paper based on the number of its citations in the first few years after publication. In order to train a citation count prediction model, we employed artificial neural network which is a powerful machine learning tool with recently growing applications in many domains including image and text processing. The empirical experiments show that our proposed method outperforms state-of-the-art methods with respect to the prediction accuracy in both yearly and total prediction of the number of citations. 相似文献