现代"体育"概念几个问题的探讨

现代"体育"概念的长期混乱有其国际上的根源、翻译上的根源和认识上的根源.对体育总概念内涵的认同和正确表述有赖于对体育各基本形态的共同特殊性进行哲学层面的分析和概括.体育总概念的某些相似概念使用频繁,亦需尽快规范.     

近几年来国外信息检索模型研究进展

信息检索模型是信息检索的核心.近几年来国外对于布尔模型的研究主要表现在对布尔模型的改进及对扩展布尔模型的进一步优化.对向量空间模型的研究,主要集中在对向量空间模型的扩展研究及对向量空间模型的应用方面.概率模型的发展主要集中在继续对概率模型进一步的研究,其与其它信息检索模型的结合,以及语言模型的研究和发展.近年来对于新兴的基于本体的信息检索模型的研究,主要集中在对基于本体的信息检索模型理论的研究,与其它检索模型的融合,以及基于本体检索模型的应用.国外信息检索模型研究的最新成果,为国内此方面的研究提供了前沿性的参考信息.     

数字图书馆个性化服务的用户建模技术论略

针对用户兴趣和偏好建立用户模型，是整个数字图书馆个性化服务系统中的关键技术。在概速数字图书馆个性化服务及其用户建模的基础上，论述了数字图书馆个性化服务用户模型的表示方法、信息来源和技术类型。     

扩号借号法的3处新例证

论文对《中图法》第4版中新发现的3处扩号借号法例证，从类级分析、并非特殊八分法类号辨析、并非加“0”类号辨析和并非下借法类号辨析等方面进行了论证。     

基于向量空间模型的主动推送系统设计与优化

主动信息服务是信息检索的发展方向之一，传统向量空间模型用于设计主动推送系统具有一定的优点，但仍不能克服检索结果不相关的问题。本文提出了一系列优化措施，设计了一个基于向量空间模型的主动推送系统原型，更好的满足网上信息检索效率的提高。     

Analysis of Statistical Question Classification for Fact-Based Questions

Question classification systems play an important role in question answering systems and can be used in a wide range of other domains. The goal of question classification is to accurately assign labels to questions based on expected answer type. Most approaches in the past have relied on matching questions against hand-crafted rules. However, rules require laborious effort to create and often suffer from being too specific. Statistical question classification methods overcome these issues by employing machine learning techniques. We empirically show that a statistical approach is robust and achieves good performance on three diverse data sets with little or no hand tuning. Furthermore, we examine the role different syntactic and semantic features have on performance. We find that semantic features tend to increase performance more than purely syntactic features. Finally, we analyze common causes of misclassification error and provide insight into ways they may be overcome.     

Simutem：一个中文信息检索系统

对一个检索系统的总体设计思想、主要实现技术作了较为具体的讨论和分析，并陈述了所做的工作。     

A dynamic decision model for portfolio investment and assets management

This paper addresses a dynamic portfolio investment problem. It discusses how we can dynamically choose candidate assets, achieve the possible maximum revenue and reduce the risk to the minimum level. The paper generalizes Markowitz's portfolio selection theory and Sharpe's rule for investment decision. An analytical solution is presented to show how an institutional or individual investor can combine Markowitz's portfolio selection theory, generalized Sharpe's rule and Value-at-Risk(VaR) to find candidate assets and optimal level of position sizes for investment (dis-investment). The result shows that the generalized Markowitz's portfolio selection theory and generalized Sharpe's rule improve decision making for investment.     

一类向量值映射与其边缘映射的次微分

本文研究拓扑线性空间上一类向量值映射与其边缘映射的次微分的关系。     

微分中值定理的推广

把微分中值定理推广到一元（行列式）函数、向量函数、抽象函数等n个方面.