共查询到19条相似文献，搜索用时 250 毫秒
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本文采用遗传算法(Genetic Algorithm,GA)实现自动组卷的系统中,并没有充分考虑试卷中知识点(测试维度)的分值分布,提出一种新的遗传算法(New Genetic Algorithm,NGA)来实现自动组卷功能,并重新定义了适应度函数,加快收敛速度。仿真实验表明,NGA算法不仅高效,且能生成一份有效试卷,使得试卷分值能在测试的维度上尽量实现均匀分布。 相似文献
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自动组卷系统是计算机辅助教学的重要组成部分,而遗传算法以其全局寻优和智能搜索的特性,得到了广泛的运用。根据自动组卷系统的特点,将遗传算法合理应用于自动组卷中,在遗传算法中,设计了双种群机制,并以试卷难度、试卷区分度、试卷的估计用时、知识点分布为基础构造适应度函数,通过轮盘赌选择方法、多点交叉和变异,较好地解决了自动组卷的多重目标寻优问题。 相似文献
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本文针对目前自动组卷系统存在试卷质量低、抽题效率低和缺乏智能性的不足,从试卷控制指标的设置、组卷的算法的设计等方面探讨如何提高自动组卷的试卷质量、速度和智能化等问题。 相似文献
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研究了自动生成试卷所需的数据结构及参数设置,提出了利用遗传算法进行试卷生成的主要设计目标,同时对试卷生成的约束条件和适应度函数进行了细致的分析。为了有效利用遗传算法实现试卷的自动生成并达到理想的结果,对遗传算法进行了改进,并成功的应用于试卷生成过程中。实践证明生成的试卷合乎要求,具有较高的可信度并取得了良好的效果。 相似文献
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运用Auto CAD内嵌的面向对象的VBA语言设计了工程制图试题库模块程序,实现了试卷的自动组卷和互动组卷功能。设计的试题库系统组题速度快,修改方便,具备良好的互动性和扩展性,并能严格保证试卷的图形标准化要求。 相似文献
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一个基于安全模型的测试用例生成工具 总被引：1，自引：0，他引：1
在基于安全评估标准的安全数据库管理系统（Security Database Management System, SDBMS）的安全功能测评中,存在的困难问题之一就是缺乏合适的测试用例.而目前基于安全产品形式化规约的测试用例自动生成方法并不能完全适用于这种需要.因为包括SDBMS在内的大多数信息安全产品的系统规约并不能真实的反映现实系统的行为,系统中的操作除了要完成其预定的功能外,同时还必须满足安全产品安全策略的约束.本文采用了基于安全产品安全策略模型的测试用例自动生成方法,设计并实现了一个测试用例自动化生成工具——CaseBuilder.该工具可针对SDBMS快速生成能够满足产品安全策略测试要求的测试用例集. 相似文献
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Richard McCreadie Shahzad Rajput Ian Soboroff Craig Macdonald Iadh Ounis 《Information processing & management》2019,56(5):1815-1836
Timeline generation systems are a class of algorithms that produce a sequence of time-ordered sentences or text snippets extracted in real-time from high-volume streams of digital documents (e.g. news articles), focusing on retaining relevant and informative content for a particular information need (e.g. topic or event). These systems have a range of uses, such as producing concise overviews of events for end-users (human or artificial agents). To advance the field of automatic timeline generation, robust and reproducible evaluation methodologies are needed. To this end, several evaluation metrics and labeling methodologies have recently been developed - focusing on information nugget or cluster-based ground truth representations, respectively. These methodologies rely on human assessors manually mapping timeline items (e.g. sentences) to an explicit representation of what information a ‘good’ summary should contain. However, while these evaluation methodologies produce reusable ground truth labels, prior works have reported cases where such evaluations fail to accurately estimate the performance of new timeline generation systems due to label incompleteness. In this paper, we first quantify the extent to which the timeline summarization test collections fail to generalize to new summarization systems, then we propose, evaluate and analyze new automatic solutions to this issue. In particular, using a depooling methodology over 19 systems and across three high-volume datasets, we quantify the degree of system ranking error caused by excluding those systems when labeling. We show that when considering lower-effectiveness systems, the test collections are robust (the likelihood of systems being miss-ranked is low). However, we show that the risk of systems being mis-ranked increases as the effectiveness of systems held-out from the pool increases. To reduce the risk of mis-ranking systems, we also propose a range of different automatic ground truth label expansion techniques. Our results show that the proposed expansion techniques can be effective at increasing the robustness of the TREC-TS test collections, as they are able to generate large numbers missing matches with high accuracy, markedly reducing the number of mis-rankings by up to 50%. 相似文献
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网上成绩管理系统已经成为很多学校管理成绩、公布成绩、查询成绩的一个重要工具。然而,网上成绩录入无疑会增加教师的工作量。如果系统能自动生成成绩质量分析表,那么网上录入成绩工作便会成为教师乐于做的事情。在自动生成质量分析表的功能里,排名是比较难实现的一部分,主要通过研究动态变量名的方式来实现排名。 相似文献
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在自行构建的超声频谱分析系统上,研究表面缺陷对声波调制的声学机理,提出一种基于单缺陷回波的局部频谱分析而对表面缺陷类型进行检测的方法,给出了用超声频域分析法对工件表面缺陷特征分析的实例,并用计算机检测系统得出了相应的试验结果,从而提高了检测可靠性.此检测方法可成为计算机辅助对缺陷进行分析的依据. 相似文献
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通过采用网络安全技术中经常使用的“报文摘要”算法．将考生的试卷内容和考生的考号进行摘要计算，然后生成一个固定长度的摘要．而考生试卷中的任何一个字节变化都会影响到该摘要，从而保证考卷的数据完整性。因此．当答卷被修改，或者考生对其答案是否被修改提出质疑时。系统会提供明确的证据。 相似文献
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《Information processing & management》2019,56(3):1133-1145
The popularity of Twitter for information discovery, coupled with the automatic shortening of URLs to save space, given the 140 character limit, provides cybercriminals with an opportunity to obfuscate the URL of a malicious Web page within a tweet. Once the URL is obfuscated, the cybercriminal can lure a user to click on it with enticing text and images before carrying out a cyber attack using a malicious Web server. This is known as a drive-by download. In a drive-by download a user's computer system is infected while interacting with the malicious endpoint, often without them being made aware the attack has taken place. An attacker can gain control of the system by exploiting unpatched system vulnerabilities and this form of attack currently represents one of the most common methods employed. In this paper we build a machine learning model using machine activity data and tweet metadata to move beyond post-execution classification of such URLs as malicious, to predict a URL will be malicious with 0.99 F-measure (using 10-fold cross-validation) and 0.833 (using an unseen test set) at 1 s into the interaction with the URL. Thus, providing a basis from which to kill the connection to the server before an attack has completed and proactively blocking and preventing an attack, rather than reacting and repairing at a later date. 相似文献
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In image retrieval, most systems lack user-centred evaluation since they are assessed by some chosen ground truth dataset. The results reported through precision and recall assessed against the ground truth are thought of as being an acceptable surrogate for the judgment of real users. Much current research focuses on automatically assigning keywords to images for enhancing retrieval effectiveness. However, evaluation methods are usually based on system-level assessment, e.g. classification accuracy based on some chosen ground truth dataset. In this paper, we present a qualitative evaluation methodology for automatic image indexing systems. The automatic indexing task is formulated as one of image annotation, or automatic metadata generation for images. The evaluation is composed of two individual methods. First, the automatic indexing annotation results are assessed by human subjects. Second, the subjects are asked to annotate some chosen images as the test set whose annotations are used as ground truth. Then, the system is tested by the test set whose annotation results are judged against the ground truth. Only one of these methods is reported for most systems on which user-centred evaluation are conducted. We believe that both methods need to be considered for full evaluation. We also provide an example evaluation of our system based on this methodology. According to this study, our proposed evaluation methodology is able to provide deeper understanding of the system’s performance. 相似文献