基于本体和加权朴素贝叶斯的网络舆情主题分类

及时准确地对舆情信息进行主题分类,不仅能实时了解舆情动态变化,还能为预判舆情发展趋势、舆论引导建立基础。本文提出一种基于本体和加权朴素贝叶斯的网络舆情主题分类方法,通过使用本体将领域知识和领域文本特征融入分类过程中。将该方法应用到动物卫生领域舆情主题分类中,分类结果精确度为0.9402,Marco_F1达到0.9339。通过与朴素贝叶斯（NB）和THUCTC两种方法的对比实验,证明本文提出的基于本体和加权朴素贝叶斯的分类方法有效且具有可行性,但是领域本体的概念、关系的完备程度会影响分类的效率。     

基于概率论的风险型决策及应用

运用概率论处理运筹学中的风险型决策问题,得到一些具有实际意义的结果：运用状态概率和方案的期望值确立风险型决策的指导原则;运用树型图直观表示风险型决策方案的形成过程;以转移概率为特征值对风险型决策方案进行稳定性分析;运用Bayes概率计算公式对决策方案进行前、后验分析和调整．     

基于贝叶斯的入侵检测

入侵检测技术在网络安全领域的应用越来越重要,它是网络安全防护的重要组成部分。提出将贝叶斯原理应用于入侵检测,把AI领域中的概念引入入侵检测,建立入侵检测的规划识别模型,尝试预测攻击者的下一步行为或攻击意图,从而起到提前预警的作用。用一实例说明了贝叶斯原理在入侵检测领域内的一些应用,提出了一个基于改进贝叶斯算法的新模型。该模型提高了入侵检测系统的完备性和准确性,能有效保障信息系统的安全。     

浅析贝叶斯分类方法在手机垃圾短信过滤系统中的应用

论述了贝叶斯分类方法在手机垃圾短信过滤系统中的应用,利用该方法对短信内容进行分类识别,从而实现对垃圾短信的有效过滤,最后对贝叶斯分类模型进行了结果分析与评估,证明该分类模型具有一定的现实可行性和可扩展性。     

The Analysis of Experimental Data: The Appreciation of Tea and Wine

A classical experiment on the tasting of tea is used to show that many standard methods of analysis of the resulting data are unsatisfactory. A similar experiment with wine is used to show how a more sensible method may be developed.     

LINEX损失函数下单边截断型分布族参数的EB检验

讨论一类这截断型分布族参数的双侧经验Bayes检验问题，文中构造了参数的经验Bayes判决函数，证明了其具有渐近最优性，并获得了收敛速度。     

Why do we need to employ Bayesian statistics and how can we employ it in studies of moral education?: With practical guidelines to use JASP for educators and researchers

In this article, we discuss the benefits of Bayesian statistics and how to utilize them in studies of moral education. To demonstrate concrete examples of the applications of Bayesian statistics to studies of moral education, we reanalyzed two data sets previously collected: one small data set collected from a moral educational intervention experiment, and one big data set from a large-scale Defining Issues Test-2 survey (DIT). The results suggest that Bayesian analysis of data sets collected from moral educational studies can provide additional useful statistical information, particularly that associated with the strength of evidence supporting alternative hypotheses, which has not been provided by the classical frequentist approach focusing on P-values. Finally, we introduce several practical guidelines pertaining to how to utilize Bayesian statistics, including the utilization of newly developed free statistical software, Jeffrey’s Amazing Statistics Program (JASP), and thresholding based on Bayes Factors (BF), to scholars in the field of moral education.     

经典人工智能算法综述

人工智能算法繁多,但经得起实践考验的经典算法有限,常见的有朴素贝叶斯、决策树、逻辑回归、支持向量机、深度学习、强化学习、遗传算法、蚁群算法、元学习等。依据人工智能算法理论基础知识,如概率统计、集合论、空间几何、图论、矩阵论等加以分类,并对相应经典人工智能算法概念和主要应用领域进行概述,去除结构细化和公式展开所带来的复杂感,揭开人工智能的神秘面纱,让算法整体轮廓得以更清晰地呈现。     

Poisson分布参数的几种估计

探讨了Poisson分布参数λ的3种估计：极大似然估计、矩估计以及Bayes估计，并对它们之间的联系和优劣性能进行了分析。     

指数分布无失效数据的Bayes估计及多层Bayes估计

本文讨论了指数分布无失效数据的失效率的先验分布为贝塔指数分布时,失效率的Bayes估计及多层Bayes估计,并给出了可靠度的估计,最后结合实际问题进行了计算,说明了估计的有效性.