LCMine: An efficient algorithm for mining discriminative regularities and its application in supervised classification

In this paper, we introduce an efficient algorithm for mining discriminative regularities on databases with mixed and incomplete data. Unlike previous methods, our algorithm does not apply an a priori discretization on numerical features; it extracts regularities from a set of diverse decision trees, induced with a special procedure. Experimental results show that a classifier based on the regularities obtained by our algorithm attains higher classification accuracy, using fewer discriminative regularities than those obtained by previous pattern-based classifiers. Additionally, we show that our classifier is competitive with traditional and state-of-the-art classifiers.     

Perceived stress,sensation seeking,and college students’ abuse of the Internet

College students (n = 140) were examined to test whether sensation seeking and perceived stress would predict abuse of the Internet. Previous studies have found that disinhibition, boredom susceptibility, and total sensation seeking scores were related to Internet abuse ( 9 and 30). Because stress has been documented to have a negative effect on students ( Pierceall & Keim, 2007), and may be linked to Internet use ( Lavoie & Pychyl, 2001), it was tested as a possible predictor of Internet abuse. This study also analyzed abuse of the Internet for sexual purposes, because sexuality is prevalent online, and college students are in an age of sexual exploration. Results of stepwise regression analyses revealed that disinhibition and total perceived stress were predictive of Internet abuse for sexual purposes, and perceived hopelessness and boredom susceptibility were predictive of Internet abuse for non-sexual purposes. Implications for students and Internet abuse are discussed.     

基于MDA数据库概念模型可视化设计

该文提出了一种基于MDA数据库概念模型可视化设计解决方案。使得数据库概念模型相当于MDA中的PIM模型;物理模型相当于MDA的PSM模型。概念模型和物理模型之间的相互转化可以自动完成。提高数据库设计的效率和数据库文档一致性。     

模式在程序设计教学中的应用

基于模式的程序设计教学方法是有益的尝试。本文分析客观存在于程序设计教学中的模式,并以算法实现级模式、程序构建级模式为例,探讨模式在程序设计教学中的应用,从思维工具、知识关联、教学效用三个方面总结这种教学新思维对于提高教学效率的作用。     

刍议马头琴的设计形态语义

马头琴不仅是蒙古族音乐文化的典型代表,它的外观形态设计同样也承载了蒙古人的信仰、历史和美学观念等,聚合了丰富的蒙古文化内涵。本文着重分析了马头琴的设计形态语义及情感形态语义,旨在引发人们对马头琴的蒙古形态语言的再思考。     

传统吉祥图案如何在现代设计中应用与发展

传统吉祥图案是中华民族文化千百年来沉淀的结果,是广大劳动人民集体的智慧与创造,是中华民族思想文化得以传承的源泉。时代的发展、变迁,物质条件及生活方式的改变,人们的观念意识和审美情趣也在不断的发生变化,与之相生相伴的各种艺术形式也都打上了鲜明的时代烙印。传统吉祥图案纹饰,变化万千,可以让我们看出当时的时代风尚,将这些传统吉祥图案认真总结,可将它归纳出主要的几种类型。     

品味童装——看图案设计在童装中的应用

图案是所有设计专业的学生在学校学习时所必修的一门专业基础课。纵观中华五千年的文明,哪一朝哪一代都有自己独特的图案风格。那么,在今天的图案设计特别是儿童服装的图案设计与应用中,怎样为孩子营造一个童话的世界,展现孩子的童真与童趣?一名优秀的童装图案设计师,应该充分利用自然环境,社会环境,民族心理和传统文化结构所赋予的条件,来解决这个问题,从而构思出独特完美而富有表现力的童装图案设计作品。     

多时间粒度序列模式挖掘

序列模式挖掘是数据挖掘的一个重要问题.传统的序列模式仅能揭示频繁出现的项目以及出现的顺序,但不能揭示在前续项目出现的情况下,后续项目出现的时间.在本文中,引入一种新的多时间粒度序列模式,模式中相邻项目之间的转换时间采用从原数据集中导出的、多时间粒度下的最小有界时间区间和平均时间标注.建立了多时间粒度序列模式挖掘模型,提出了一种新的多时间序列模式挖掘算法MG-PrefixSpan.实验表明,算法是有效的.     

一种基于子串识别的多模式串匹配算法

多模式串匹配算法是网络内容过滤系统的核心技术。巨大的存储空间开销是制约多模式匹配串算法应用的瓶颈之一。提出一种基于子串识别的多模式匹配算法—HashBOM,该算法利用位哈希表存储模式串的子串信息以大幅度减少存储空间,利用递归哈希函数计算字符串的哈希值以实现快速匹配。理论分析表明,该算法的空间复杂度为O(rm~2),优于基于子串识别的匹配算法BOM的空间复杂度O(mr|∑|log_2mr);该算法搜索匹配过程的平均时间复杂度为O(nlog|∑|)mr/m,与BOM算法相同(其中m为最短模式串的长度,r为模式串的个数,n为待匹配文本的长度,|∑|为字母表的大小)。在随机数据集和真实数据集上的实验表明,该算法的存储空间远远低于BOM算法,而匹配速度与BOM算法相当,非常适合在线实时匹配的应用环境。     

Maintaining consistent results of continuous queries under diverse window specifications

Continuous queries applied over nonterminating data streams usually specify windows in order to obtain an evolving–yet restricted–set of tuples and thus provide timely and incremental results. Although sliding windows get frequently employed in many user requests, additional types like partitioned or landmark windows are also available in stream processing engines. In this paper, we set out to study the existence of monotonic-related semantics for a rich set of windowing constructs in order to facilitate a more efficient maintenance of their changing contents. After laying out a formal foundation for expressing windowed queries, we investigate update patterns observed in most common window variants as well as their impact on adaptations of typical operators (like windowed join, union or aggregation), thus offering more insight towards design and implementation of stream processing mechanisms. Furthermore, we identify syntactic equivalences in algebraic expressions involving windows, to the potential benefit of query optimizations. Finally, this framework is validated for several windowed operations against streaming datasets with simulations at diverse arrival rates and window specifications, providing concrete evidence of its significance.