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991.
针对网络信息用户的网络迷失、认知负荷超载以及浏览路径失控等问题,基于对有意义学习及概念地图理论的应用分析,对建立适应性网络浏览路径控制机制以提高网络信息服务系统质量的基本思路和方法进行探讨,以期为更深入研究和有效解决网络信息服务系统质量问题提供参考和借鉴。 相似文献
992.
谈谈数学建模能力培养的阶段性与题目的层次性 总被引:7,自引:1,他引:6
中学数学建模活动的开展对中学生数学素养的提高起到了积极作用.但在中学开展数学建模活动一定要结合中学生的年龄特点、知识结构和智力水平,结合正常教学的教材内容,分层次逐步推进.因此,学生的数学建模能力应分阶段培养,建模题目也应划分不同层次,从而达到面向全体学生,提高创造能力的目的. 相似文献
993.
994.
The paper describes the application of an ANN-based approach to the identification of the parameters relevant to the steady-state
behavior of composite power electronic device models of circuit simulation software. The identification of model parameters
of IGBT in PSPICE using BP neural network is illustrated. 相似文献
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[目的/意义] 归纳总结现有国外图书馆数字馆藏建设游戏项目的实践特点和成功经验,以期为国内图书馆开发设计数字馆藏建设游戏项目提供参考和借鉴。[方法/过程] 综合运用网络调研法和案例分析法,以数字馆藏建设的准备、实施和维护3个阶段为基础,系统地梳理当前国外图书馆馆藏建设中游戏项目的应用形式和实践进展,并以大型开源游戏服务平台——Metadata Game为例,深入剖析该数字馆藏建设游戏项目的基本概况、技术基础、实现机理以及操作方法等内容,从而总结出国外图书馆数字馆藏建设游戏项目的主要特点及经验启示。[结果/结论] 我国图书馆可借鉴国外游戏项目的经验,根据特定建设需要和自身技术条件,在数字馆藏建设项目中逐步引入不同类型、主题及形式的游戏项目。 相似文献
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Motivation plays a critical role in human behavior and is particularly important during college, where a single class can make or break an academic career. The longitudinal research on expectancies for success and utility value primarily focuses on prediction or change over many years, rather than change over a short period of time. However, a single class in college can often be the difference between getting a degree or not. To better understand how motivation progresses in the short-term, we examined changes in expectancy and utility value simultaneously during a single college class. Both constructs declined during the class and showed significant variability across individuals. In addition, change in expectancy was strongly correlated with change in utility value, and the expectancy slope estimates were significant predictors of continuing interest. We discuss the need for a better understanding of short-term dynamic relationships between expectancies, utility value, and outcomes. 相似文献
1000.
Ximing Li Ang Zhang Changchun Li Jihong Ouyang Yi Cai 《Information processing & management》2018,54(6):1345-1358
Topic models often produce unexplainable topics that are filled with noisy words. The reason is that words in topic modeling have equal weights. High frequency words dominate the top topic word lists, but most of them are meaningless words, e.g., domain-specific stopwords. To address this issue, in this paper we aim to investigate how to weight words, and then develop a straightforward but effective term weighting scheme, namely entropy weighting (EW). The proposed EW scheme is based on conditional entropy measured by word co-occurrences. Compared with existing term weighting schemes, the highlight of EW is that it can automatically reward informative words. For more robust word weight, we further suggest a combination form of EW (CEW) with two existing weighting schemes. Basically, our CEW assigns meaningless words lower weights and informative words higher weights, leading to more coherent topics during topic modeling inference. We apply CEW to Dirichlet multinomial mixture and latent Dirichlet allocation, and evaluate it by topic quality, document clustering and classification tasks on 8 real world data sets. Experimental results show that weighting words can effectively improve the topic modeling performance over both short texts and normal long texts. More importantly, the proposed CEW significantly outperforms the existing term weighting schemes, since it further considers which words are informative. 相似文献