零售型企业的供应商分类管理研究

供应链管理是企业在当前日益激烈的竞争环境中为提高核心竞争力而形成发展起来的管理方法。供应商的选择与管理是供应链管理中的研究热点,尤其是在零售领域。一个零售商往往拥有众多的供应商,对这些供应商进行分类管理是降低运营成本、提高管理水平的重要途径。此外,对供应商进行分类管理还能够促进双方在更深层面上的战略性合作,通过互动交流提高整体运作绩效。本文通过对不同类型供应商的比较分析指出,将供应商按产品优势和服务优势进行二元分类最能体现供应商间的本质性区别,并且也是管理成本相对最低的分类方法,我们以其各自的突出优势点将供应商分为产品型供应商与服务型供应商两类。本文根据零售型企业的供应商特点给出了供应商分类的指标集,并利用判别分析给出了相应的定量化分类方法及应用实例。     

Convergence rates of generalization errors for margin-based classification

This paper develops a general approach to quantifying the size of generalization errors for margin-based classification. A trade-off between geometric margins and training errors is exhibited along with the complexity of a binary classification problem. Consequently, this results in dealing with learning theory in a broader framework, in particular, of handling both convex and non-convex margin classifiers, among which includes, support vector machines, kernel logistic regression, and ψ$\psi$-learning. Examples for both linear and nonlinear classifications are provided.     

农民“反行为”何以可能?——以产权认知与物的分类为视角

河东村农民中盛行的偷盗铁矿石、私自开铁矿等"反行为"的背后蕴含着丰富的社会文化意涵。在对铁矿归属的认定上,农民的观念与法定产权之间存在冲突,即农民具有独特的产权认知。进而,这一产权认知嵌于农民在日常实践中形成的"物的分类"图式,而这一图式是塑造农民行为的深层社会文化背景。可见,农民认知与行为方式受到地方性知识与内生秩序的影响。我们必须超越理性小农和生存伦理的假定,在特定文化情境中揭示农民的行为动因,以其本土实践来理解他们的生活世界。     

Adaptive kernel scaling support vector machine with application to a prostate cancer image study

The support vector machine (SVM) is a popularly used classifier in applications such as pattern recognition, texture mining and image retrieval owing to its flexibility and interpretability. However, its performance deteriorates when the response classes are imbalanced. To enhance the performance of the support vector machine classifier in the imbalanced cases we investigate a new two stage method by adaptively scaling the kernel function. Based on the information obtained from the standard SVM in the first stage, we conformally rescale the kernel function in a data adaptive fashion in the second stage so that the separation between two classes can be effectively enlarged with incorporation of observation imbalance. The proposed method takes into account the location of the support vectors in the feature space, therefore is especially appealing when the response classes are imbalanced. The resulting algorithm can efficiently improve the classification accuracy, which is confirmed by intensive numerical studies as well as a real prostate cancer imaging data application.     

基于语料和基于标引经验的自动分类模式比较

从原理、系统设计、知识库构建、分类算法、性能等方面对自动分类的两种模式———基于训练语料和基于人工标引经验———进行介绍和比较,这两种分类模式都具有一定的可行性。基于训练语料的自动分类模式完全依靠机器学习从训练集中发现类目的特征,数学论证充分,易于维护,比较适合于面向行业和主题的粗分类,但是过分强调了机器学习的效能,忽略了人工智力劳动成果的利用,训练过程和分类过程运算量,算法复杂;而基于标引经验的自动分类模式利用简单的统计学方法从书目数据库中挖掘人工标引经验,适用于面向体系分类法的详细分类,分类算法简单,运算量小,但过分依赖经验,缺乏有说服力的数学证明。知识库的完备性和合理性是影响两者分类效能的主要因素,是两者面临的共同问题。     

论文体分类及实用文章与文学作品的本质特征——“文章三级次分类新体系”评说

朱广贤先生提出的“两门——八类——多体”的文章三级次分类新体系，是比较科学的文体分类法，理当引起学界的重视。这一分类法弘扬了中国古代文体研究的理论成果，对于现当代文体研究的偏蔽无疑是个有力的冲击，亦可纠正我国现当代语文教育中文体分类的混乱状况，有利于现代写作学科的理论建设。朱广贤先生有关“文学作品门”和“实用文章门”本质、特征的论断，别开生面，但有语焉不详之憾，有些论断也未必尽然，因此彰显其说之真、弥补其说之不足，使之臻于完善，实属必要。     

Strong laws of large numbers for dependent heterogeneous processes: a synthesis of recent and new results

This paper surveys recent developments in the strong law of large numbers for dependent heterogeneous processes. We prove a generalised version of a recent strong law for Lz-mixingales, and also a new strong law for Lpmixingales. These results greatly relax the dependence and heterogeneity conditions relative to those currently cited, and introduce explicit trade-offs between dependence and heterogeneity. The results are applied to proving strong laws for near-epoch dependent functions of mixing processes. We contrast several methods for obtaining these results, including mapping directly to the mixingale properties, and applying a truncation argument.     

Applying classification algorithms in practice

In this paper we present a perspective on the overall process of developing classifiers for real-world classification problems. Specifically, we identify, categorize and discuss the various problem-specific factors that influence the development process. Illustrative examples are provided to demonstrate the iterative nature of the process of applying classification algorithms in practice. In addition, we present a case study of a large scale classification application using the process framework described, providing an end-to-end example of the iterative nature of the application process. The paper concludes that the process of developing classification applications for operational use involves many factors not normally considered in the typical discussion of classification models and algorithms.     

DISTRIBUTION OF THE LEAST SQUARES ESTIMATOR IN A FIRST-ORDER AUTOREGRESSIVE MODEL

This paper investigates the finite sample distribution of the least squares estimator of the autoregressive parameter in a first-order autoregressive model. A uniform asymptotic expansion for the distribution applicable to both stationary and nonstationary cases is obtained. Accuracy of the approximation to the distribution by a first few terms of this expansion is then investigated. It is found that the leading term of this expansion approximates well the distribution. The approximation is, in almost all cases, accurate to the second decimal place throughout the distribution. In the literature, there exist a number of approximations to this distribution which are specifically designed to apply in some special cases of this model. The present approximation compares favorably with those approximations and in fact, its accuracy is, with almost no exception, as good as or better than these other approximations. Convenience of numerical computations seems also to favor the present approximations over the others. An application of the finding is illustrated with examples.     

《说文》"同意"说评述

"同意"是<说文>体例研究中的重要内容之一.在前人的研究中,有的学者误把"同意"作为六书之一的转注,同意是指构字的笔意相同,与造字法之一的转注无涉.在同意体例中有"某与某同"一类,前人有匡正字体之说,许慎所说"某与某同"实际是要求人们借此以求笔意,"同意"和"某与某同"都是用两个或两个以上的字相互发明来揭示笔意的.在前人对同意体例内部的分类上尚存在分歧,这也说明前人对同意体例缺乏全面而又深入的研究.凡此种种,只有对<说文>同意体例作深入而全面的研究,才能正确认识同意体例的作用.