高校二级学院办学初探

本文阐述了二级学院的特点、运转情况、产生的必然性和积极作用、目前存在的问题及今后的展望     

从英汉比较语言学角度分析英语习语特征

本文从比较语言学角度分析了英语习语特征，着重对英汉习语各自的特点进行了归纳。了解这些共性和差异，对于语言学习，特别是跨文化意识的培养具有非常重要的意义。     

贵州韭菜坪石林形态差异性分析

在对贵州韭菜坪石林进行采样测量的基础上,根据石林形态的相似性和差异性对石林形态进行了分区,分析了不同微地貌部位石林形态特征的差异性以及影响石林形态差异的主要因素。同时,根据石林形态的测量数据,对石林形态进行了计量分析,结果也显示了不同地貌部位之间石林形态的差别,方差检验的结果也表明了韭菜坪石林形态的差异性是由于地貌和岩性构造等因素造成的。     

日本成人教育特色及借鉴

日本成人教育的发展形成了自己鲜明的特色：立法制度完备,多元的机构设置,重视师资培训,开放、灵活的招生与教学方式,专业设置紧跟时代步伐等。我国的成人教育要获得进一步发展,应该借鉴其先进经验,从教育立法、机构设置、师资培训、入学与教学方式及专业设置等五个方面进行改革。     

Information gain and divergence-based feature selection for machine learning-based text categorization

Most previous works of feature selection emphasized only the reduction of high dimensionality of the feature space. But in cases where many features are highly redundant with each other, we must utilize other means, for example, more complex dependence models such as Bayesian network classifiers. In this paper, we introduce a new information gain and divergence-based feature selection method for statistical machine learning-based text categorization without relying on more complex dependence models. Our feature selection method strives to reduce redundancy between features while maintaining information gain in selecting appropriate features for text categorization. Empirical results are given on a number of dataset, showing that our feature selection method is more effective than Koller and Sahami’s method [Koller, D., & Sahami, M. (1996). Toward optimal feature selection. In Proceedings of ICML-96, 13th international conference on machine learning], which is one of greedy feature selection methods, and conventional information gain which is commonly used in feature selection for text categorization. Moreover, our feature selection method sometimes produces more improvements of conventional machine learning algorithms over support vector machines which are known to give the best classification accuracy.     

基于Gabor小波的人脸识别系统的实现

给出了一种基于Gabor小波的人脸识别系统的实现.该方法先利用模板匹配法定位人脸图像的眼睛,然后经过标准化使图像具有相同的基准,其余特征点的搜索采用弹性图匹配方法;特征点的粗略位置根据训练集的人脸结构知识定位,然后使用弹性图簇的数据结构求得特征点的精确位置,当各特征点的精确位置定位后,人脸的Gabor Jets就可求得;样本图像的相似程度可用与人脸特征点对应的GaborJets作度量函数表达.     

简析“天津市治安维持会”的基本特征

1937年8月1日成立的天津市治安维持会,是日本侵略军在华北占领区最早扶植建立的傀儡组织之一。该伪组织遵照日军意旨,临时代行天津市府职权,在协助日军维持战争初期社会治安、镇压抗日活动等方面发挥了重要作用。本文分析天津市治安维持会的基本特征,如人员构成上的复杂性,政治上的对日依附性,行政上的准政府性,活动内容的示范性,组织上的过渡性等,以期读者对该伪组织的反动本质有进一步地了解和认识。     

一种基于文本语义的网络敏感话题识别方法

网络已成为当今世界重要的信息载体,但是网络信息良莠不齐,对人们的生活造成了很多负面影响,因此,如何正确识别网络中的敏感话题,是当前网络舆情分析与监管的重要任务之一。本文以识别网络论坛中的敏感话题为目标,基于网络论坛文本在结构和表达上表现出的篇幅短、结构不完整、文字口语化等特性,将该类文本表示成基于向量空间模型的文本矩阵,并根据网络敏感话题具有先验知识和态度倾向性等特点,提出了基于倾向性词典的特征提取方法,可有效提高网络敏感话题识别的正确率,最后通过实验验证了这一改进的有效性,证实了本文的研究价值。     

黄自歌曲钢琴伴奏之音乐特色研究

黄自为其创作的歌曲谱写的钢琴伴奏曲是其声乐作品的重要组成部分,它不仅能烘托旋律的意境,同时还能激发演唱者的表演欲望。其钢琴伴奏曲具有古典主义与浪漫主义风格相融合,诗、歌、乐完美结合,浓郁的民族风格等音乐特色。     

Sentiment aggregation of targeted features by capturing their dependencies: Making sense from customer reviews

Ideation is an important phase in the new product development process at which product designers innovate and select novel ideas that can be added as features to an existing product. One way to find novel ideas is to transfer uncommon features of products of other domains and integrate them into the product to be improved. However, before incorporating such targeted features into the product, they need to be evaluated against the customers’ acceptance in social media using sentiment aggregation tools. Despite the many studies in sentiment analysis, mapping the customers’ opinions towards both high-level and technical features of a product extracted from social media to their best corresponding component in that product is still a challenge. Furthermore, none of the existing approaches ascertains the sentiment value of a targeted feature by capturing its dependencies on other features. In this paper, to address these drawbacks, we propose the sentiment aggregation framework for targeted features (SA-TF). SA-TF determines the sentiment of a targeted feature by assisting product designers in the tasks of mapping the features discussed in the reviews to the right product components, sentiment aggregation and considering feature dependencies to determine their polarity. The superiority of the different phases of SA-TF is demonstrated with experiments and comparing it with an existing approach.