论拓跋鲜卑民族的融合

化上的转变是完成民族融合的重要一步,这种转变促使了拓跋鲜卑民族成员社会心理与社会行为的变化。对汉化进一步“内化”的结果,使鲜卑人原初的民族意识逐渐消失、新的民族意识日益形成,当入主中原的拓跋鲜卑民族形成了与汉族相同的民族意识之后,就意味着二之间的融合已经完成,因此,民族意识的转化是考察民族融合的关键。     

企业数据库体系化环境及建设

信息化建设是目前企业为提高自身竞争而正在做的一项重要工作，企业信息化的目的就是要让自己和服务对象能及时获得所需要的信息，以调整和控制企业的运营，为用户提供更好的产品和服务，章从企业数据环境的角度，给出了企业数据库体系化环境的概念，说明了各层次数据库的作用，探讨了数据库体系化环境的建设。     

数据挖掘技术在客户关系管理中的应用研究

客户关系管理以客户为中心,深入研究客户行为,通过客户关怀提高客户满意度,进而提高企业的竞争力。而数据挖掘技术则为客户关系管理提供了强有力的技术支持。文章阐述了数据挖掘技术在客户关系管理中应用的研究背景和意义,并介绍了客户关系管理思想、数据挖掘的过程和方法、以及数据挖掘技术在客户关系管理中的应用。     

An empirical investigation of factors influencing the adoption of data mining tools

Previous studies explored the adoption of various information technologies. However, there is little empirical research on factors influencing the adoption of data mining tools (DMTs), particularly at an individual level. This study investigates how users perceive and adopt DMTs to broaden practical knowledge for the business intelligence community. First, this study develops a theoretical model based on the Technology Acceptance Model 3, and then examines its perceived usefulness, perceived ease of use, and its ability to explain users’ intentions to use DMTs. The model's determinants include 4 categories: the task-oriented dimension (job relevance, output quality, result demonstrability, response time, and format), control beliefs (computer self-efficacy and perceptions of external control), emotion (computer anxiety), and intrinsic motivation (computer playfulness). This study also surveys the moderating effect of experience and output quality on the determinants of DMT adoption and use. An empirical study involving 206 DMT users was conducted to evaluate the model using structural equation modeling. Results demonstrate that the proposed model explains 58% of the variance. The findings of this study have interesting implications with respect to DMT adoption, both for researchers and practitioners.     

林语堂MomentinPeking的翻译主体间性探究

在翻译活动中,只有相互作用的主体（译者、原作者和读者）平等交流和对话,才会取得成功的翻译。从视域融合视角出发,对林语堂先生所著Moment1nPeklng的三个译本进行对比分析．探讨主体词性在翻译过程中的体现和影响,对指导翻译活动有一定的意义。     

异构数据库数据迁移研究

数据迁移是指将一种数据环境中的数据根据需要进行某种转换,导入另外一种相异或者相同的数据环境中。异构数据库迁移是指将数据库管理系统中不同的,或者数据结构、数据组成与定义相异的数据之间尽量进行等价、无损的数据转移。通过文献案例和理论研究对异构数据库的迁移技术进行了分析,提出了一种以Java为编程语言和数据库结构JDBC为基础的异构数据库管理系统的迁移方法,并通过实验证实了此方法的有效性。     

Web数据挖掘在急性高原病易感人群预测中的应用

将Web数据挖掘技术应用于急性高原病易感人群的预测中,通过Web技术与数据挖掘技术相结合,将分散于Web中的数据经过检索、清洗、处理后存储在专门的数据仓库中。在现有研究成果的基础上,提出一个简便、高效的急性高原病易感人群预测模型。     

高职《数据结构》教学改革与探索

“数据结构”是计算机专业中一门重要的专业基础课程,同时又是计算机专业中一门难教和难学的课程。本文针对高职生源的实际情况,探索对该课程的教材、教学内容、教学方法、实验等方面进行改革,以提高该门课的教学效果。     

城市规划专题信息数据标准化研究

从现有城市规划数据的数据分类、数据代码、数据标准、数据报告入手,结合城市用地国家分类标准进行分析,提出一种包括专题规划信息分类、数据编码、数据分层的规划专题信息数据标准化技术。     

Adaptive multi-feature fusion via cross-entropy normalization for effective image retrieval

Multi-feature fusion has achieved gratifying performance in image retrieval. However, some existing fusion mechanisms would unfortunately make the result worse than expected due to the domain and visual diversity of images. As a result, a burning problem for applying feature fusion mechanism is how to figure out and improve the complementarity of multi-level heterogeneous features. To this end, this paper proposes an adaptive multi-feature fusion method via cross-entropy normalization for effective image retrieval. First, various low-level features (e.g., SIFT) and high-level semantic features based on deep learning are extracted. Under each level of feature representation, the initial similarity scores of the query image w.r.t. the target dataset are calculated. Second, we use an independent reference dataset to approximate the tail of the attained initial similarity score ranking curve by cross-entropy normalization. Then the area under the ranking curve is calculated as the indicator of the merit of corresponding feature (i.e., a smaller area indicates a more suitable feature.). Finally, fusion weights of each feature are assigned adaptively by the statistically elaborated areas. Extensive experiments on three public benchmark datasets have demonstrated that the proposed method can achieve superior performance compared with the existing methods, improving the metrics mAP by relatively 1.04% (for Holidays), 1.22% (for Oxf5k) and the N-S by relatively 0.04 (for UKbench), respectively.