数据挖掘中属性项压缩的统计方法研究

文章试图将统计思想与(Rough)粗糙集理论相结合,针对事务性数据库属性项压缩问题提出了一些行之有效的方法,即基于重要性的属性压缩、基于相依性的属性压缩、属性项的广义线形分析及压缩、基于多重相关性的属性项压缩,以此达到数据库压缩之目的。     

The German Administrative Record Census – An object identification problem

Summary: The next German census will be an Administrative Record Census. Data from several administrative registers about persons will be merged. Object identification has to be applied, since no unique identification number exists in the registers. We present a two–step procedure. We briefly discuss questions like correctness and completeness of the Administrative Record Census. Then we focus on the object identification problem, that can be perceived as a special classification problem. Pairs of records are to be classified as matched or not matched. To achieve computational efficiency a preselection technique of pairs is applied. Our approach is illustrated with a database containing a large set of consumer addresses.*This work was partially supported by the Berlin–Brandenburg Graduate School in Distributed Information Systems (DFG grant no. GRK 316). The authors thank Michael Fürnrohr for previewing the paper. We would like to thank also for the helpful comments of an anonymous reviewer.     

初探当前知识经济下企业文化发展的新趋向

当前知识经济给企业组织管理带来了新的变化,对其企业文化发展产生了深刻影响,培养核心竞争力已成为企业制胜的关键。塑造学习型组织与超越文化、经济人与道德人完美结合等已成为企业文化发展的新趋势。     

Propensity score prediction for electronic healthcare databases using super learner and high-dimensional propensity score methods

ABSTRACT

The optimal learner for prediction modeling varies depending on the underlying data-generating distribution. Super Learner (SL) is a generic ensemble learning algorithm that uses cross-validation to select among a ‘library’ of candidate prediction models. While SL has been widely studied in a number of settings, it has not been thoroughly evaluated in large electronic healthcare databases that are common in pharmacoepidemiology and comparative effectiveness research. In this study, we applied and evaluated the performance of SL in its ability to predict the propensity score (PS), the conditional probability of treatment assignment given baseline covariates, using three electronic healthcare databases. We considered a library of algorithms that consisted of both nonparametric and parametric models. We also proposed a novel strategy for prediction modeling that combines SL with the high-dimensional propensity score (hdPS) variable selection algorithm. Predictive performance was assessed using three metrics: the negative log-likelihood, area under the curve (AUC), and time complexity. Results showed that the best individual algorithm, in terms of predictive performance, varied across datasets. The SL was able to adapt to the given dataset and optimize predictive performance relative to any individual learner. Combining the SL with the hdPS was the most consistent prediction method and may be promising for PS estimation and prediction modeling in electronic healthcare databases.     

汽车车灯零部件产品数据库管理系统

用Ａｃｃｅｓｓ９７软件研制开发了一套应用于企业产品信息管理的数据库管理系统,实现了产品信息管理的必要功能。     

Evaluation of Embedded Intelligent Real‐time Systems*

Over the past two decades, questions have surfaced about the effectiveness and contribution of intelligent systems to decision makers in a variety of settings. This paper focuses on the evaluation challenges associated with intelligent real‐time software systems that are embedded in larger host systems. With the proliferation of such systems in operational settings such as aerospace, medical, manufacturing, and transportation systems, increased attention to evaluations of such systems, and to resulting software safety, is warranted. This paper describes one such evaluation and proposes a set of evaluation criteria for embedded intelligent real‐time systems (EIRTS). Implications of the evaluation and the evaluation criteria are discussed.     

血亲情理还是理性主义--中西方德性与知识研究视角透视

知性在西方的哲学中是一个认识论的概念,是理性在意识中的思辨反思,是感觉知觉的综合而形成的概念能力向度。但一旦当知性所欲求的知识与力的冲动相联系而具有伦理精神,其德性的形成即具有理性主义的特征,或者说,知识与德性之间也形或了概念话语的某种关系的张力,在西方,倾向于德性的理性主义,在东方则是知识的德性主义,或说知性德性、而在中国古代,没有知性的概念,和古希腊一样是以知和智实现向德性的转换。但是由于传统心性儒家赋予知或智以道德情感,心性相融本身已经祛魅知识在德性形成中的作用,甚至其知行合一预示了对道德行为的漠视。而萄予与心性儒宋不同,心无德蕴涵了对知识的渴求和转知成德的期望,其复反其初的知性思维把知识与德性的关系嵌入行为的践援之中,而其现实主义品格、实践理性的精神又隐分了对德性的尊重并且把知识与伪相结合赋予知性分的特埂及其追求义利和谐、德得相通的和一特征。     

Anchoring Economic Predictions in Common Knowledge

The paper examines within a unified methodology expectational coordination in a series of economic models. The methodology views the predictions associated with the Rational Expectations Hypothesis as reasonable whenever they can be derived from the more basic Common Knowledge Hypothesis. The paper successively considers a simple non‐noisy N‐dimensional model, standard models with “intrinsic” uncertainty, and reference intertemporal models with infinite horizon. It reviews existing results and suggests new ones. It translates the formal results into looser but economically intuitive statements, whose robustness, in the present state of knowledge, is tentatively ascertained.     

大学生个性培养与素质教育

知识经济要求素质教育应注重大学生个性的培养和发展 ,创新精神是素质教育的核心 ,注重个性的正确引导和培养是培养大学生创新精神的前提和有效方式。现行的教育方式缺乏个性培养 ,扼制了创新精神的树立和创新能力的发展 ,需要下大力气予以改进和提高。     

Learning How and Learning What: Effects of Tacit and Codified Knowledge on Performance Improvement Following Technology Adoption

This paper examines effects of tacit and codified knowledge on performance improvement as organizations gain experience with a new technology. We draw from knowledge management and learning curve research to predict improvement rate heterogeneity across organizations. We first note that the same technology can present opportunities for improvement along more than one dimension, such as efficiency and breadth of use. We compare improvement for two dimensions: one in which the acquisition of codified knowledge leads to improvement and another in which improvement requires tacit knowledge. We hypothesize that improvement rates across organizations will be more heterogeneous for dimensions of performance that rely on tacit knowledge than for those that rely on codified knowledge (H1), and that group membership stability predicts improvement rates for dimensions relying on tacit knowledge (H2). We further hypothesize that when performance relies on codified knowledge, later adopters should improve more quickly than earlier adopters (H3). All three hypotheses are supported in a study of 15 hospitals learning to use a new surgical technology. Implications for theory and practice are discussed.