Research on the Teaching Reform of “Big Data Analysis and Visualization” Course for College Students

Under the background of the big data era,the education of big data majors is undergoing a profound teaching reform and innovation.With the increasing role of big data technology in analysis and decision-making,updating and expanding the teaching content of big data majors has become particularly important.In the era of big data,modern enterprises have put forward new and higher demands for big data talents,which not only include traditional data analysis skills but also knowledge of data visualization and information technology.To address these challenges,big data education needs to reform and innovate in the development and utilization of teaching content,methods,and resources.This paper proposes teaching models and reform methods for big data majors and analyzes corresponding teaching reforms and innovations to meet the requirements of the new development of big data majors.The traditional classroom teaching method is no longer sufficient to meet the learning needs of students,and more dynamic and interactive teaching methods,such as case studies,flipped classrooms,and project-based learning,are becoming increasingly essential.These innovative teaching methods can more effectively cultivate students’practical operation skills and independent thinking while allowing them to better learn advanced knowledge in a real big-data environment.In addition,the paper also discusses the construction of big data processing and analysis platforms,as well as innovative teaching management and evaluation systems to improve teaching quality.

Application Analysis of Nursing Students'Grades in Course Relevance Based on Association Rule Mining Algorithm Apriori

By analyzing the correlation between courses in students’grades,we can provide a decision-making basis for the revision of courses and syllabi,rationally optimize courses,and further improve teaching effects.With the help of IBM SPSS Modeler data mining software,this paper uses Apriori algorithm for association rule mining to conduct an in-depth analysis of the grades of nursing students in Shandong College of Traditional Chinese Medicine,and to explore the correlation between professional basic courses and professional core courses.Lastly,according to the detailed analysis of the mining results,valuable curriculum information will be found from the actual teaching data.

Hydraulic metal structure health diagnosis based on data mining technology

In conjunction with association rules for data mining, the connections between testing indices and strong and weak association rules were determined, and new derivative rules were obtained by further reasoning. Association rules were used to analyze correlation and check consistency between indices. This study shows that the judgment obtained by weak association rules or non-association rules is more accurate and more credible than that obtained by strong association rules. When the testing grades of two indices in the weak association rules are inconsistent, the testing grades of indices are more likely to be erroneous, and the mistakes are often caused by human factors. Clustering data mining technology was used to analyze the reliability of a diagnosis, or to perform health diagnosis directly. Analysis showed that the clustering results are related to the indices selected, and that if the indices selected are more significant, the characteristics of clustering results are also more significant, and the analysis or diagnosis is more credible. The indices and diagnosis analysis function produced by this study provide a necessary theoretical foundation and new ideas for the development of hydraulic metal structure health diagnosis technology.

The analysis of application of data mining technology in the system of intrusion detection

With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Internet has the features of interaction, openness, sharing and so on. However, during the daily commerce, people worry about the security of the network system. So a new technology which can detect the unusual behavior in time has been invented in order to protect the security of network system. The system of intrusion detection needs a lot of new technology to protect the data of the network system. The application of data mining technology in the system of intrusion detection can provide a better assistant to the users to analyze the data and improve the accuracy of the checking system.

Research on the Data Mining Technology in College Students'Attendance System Based on the Big Data Architecture

With the development and improvement of the information technologies,the increasing of the upper application systems and the rapid expansion of the data accumulated in the campus information environment,a typical campus big data environment has initially been formed.Because of the characteristics of the higher education,students'mobility is great and their learning environment is uncertain,so that the students'attendance mostly used the manual naming.The student attendance system based on the big data architecture is relying on the campus network,and adopting the appropriate sensors.Through the data mining technology,combined with the campus One Card solution,we can realize the management of the attendance without naming in class.It can not only strengthen the management of the students,but can also improve the management levels of the colleges and universities.

Research on the big data feature mining technology based on the cloud computing

The cloud computing platform has the functions of efficiently allocating the dynamic resources, generating the dynamic computing and storage according to the user requests, and providing the good platform for the big data feature analysis and mining. The big data feature mining in the cloud computing environment is an effective method for the elficient application of the massive data in the information age. In the process of the big data mining, the method o f the big data feature mining based on the gradient sampling has the poor logicality. It only mines the big data features from a single-level perspective, which reduces the precision of the big data feature mining.

Research on the Development of Ideological and Political Education Resources for College Students Based on the Data Mining Technology

With the rapid development of the computer technologies, the rapid spread and development of the network resources have a significant impact on people's thinking and lifestyle. The ideological and political education in colleges and universities should keep pace with the times, and examine the new ways and resources of the ideological and political education in colleges and universities from the perspective of the times. The high-tech has been applied to the development of the modem education, expanding the teaching space-time, improving the teaching methods of the ideological and political course, and enriching the teaching contents of the ideological and political theoretical courses. The development mechanism of the ideological and political education resources for college students based on the data mining technology is not only in line with the trend of the times, but can also play an ideal role in optimizing the ideological and political education mechanism for college students.

The application of data mining technology in data service of micro service architecture

This paper introduces the application of data mining technology in data service. Data mining is a new technology, but its application time is long, and the application effect is obvious. Data mining technology can be used in enterprise customer service system, which can help enterprises to find potential customers, while retaining the most valuable customers. We pointed out the necessity of establishing data mining technology and service intelligence analysis system based on the combination of intelligence analysis and service characteristics and processes, the method of data mining, knowledge management ideas applied to intelligence analysis and service system.

Analysis on The Application of Data Mining Technology in Computer Network Virus Defense

With the rapid development of computer network,the society has entered the information and digital era,it plays an important role in speeding up the pace of social development and providing more convenient services for people.However, the security problem of computer network is becoming more and more serious. All kinds of network viruses pose a great threat to the security of computer network.As the most advanced data processing technology currently, data mining technology can effectively resist the invasion of network virus to computer system,and plays an important role in improving the security of the computer network.This paper starts with the concept of data mining technology and the characteristics of computer network virus,and makes an in-depth analysis on the specific application of data mining technology in the computer network virus defense.

Research on the Big Data Cloud Computing Based on the Network Data Mining

The big data cloud computing is a new computing mode,which integrates the distributed processing,the parallel processing,the network computing,the virtualization technology,the load balancing and other network technologies.Under the operation of the big data cloud computing system,the computing resources can be distributed in a resource pool composed of a large number of the computers,allowing users to connect with the remote computer systems according to their own data information needs.

基于数据挖掘的前沿技术识别方法与实证研究

依据前沿技术的前瞻性、先导性、探索性及颠覆性特征,构建基于数据挖掘的前沿技术识别方法,可为高效制定技术发展策略、合理调整技术规划布局提供支撑。首先,以工程索引(engineering index,EI)和德温特创新(Derwent innovation,DI)平台数据库为数据源,制定检索表达式采集数据,并对数据进行预处理。其次,建立表征前沿技术特征的指标体系,并对据此筛选出的技术文本数据进行挖掘,识别前沿技术主题。最后,以量子计算领域为例开展实证研究,识别出量子纠错技术、光量子芯片技术等前沿技术点,经技术专家等验证,表明识别结果科学有效。

基于“教赛协同”的数据挖掘课程教学改革研究

数据挖掘课程是大数据和人工智能方向重要的核心课程,主要培养学生在数据驱动的范式下结合问题场景和社会需求,具备利用数据挖掘方法和技术分析、解决实际问题的能力。针对数据挖掘课程教学过程中存在的“痛点”问题,以培养工程型创新性人才为导向,从课程内容体系、学科竞赛体系和课程队伍体系三个维度,探索并构建基于“教赛协同”的数据挖掘课程教学改革的策略和方法,为地方高等院校大数据和人工智能相关专业的发展提供思路。

基于BP神经网络模型的矿井生产预警技术研究

矿井生产具有高动态、快时变、混沌和随机特点,生产过程中的人、设备、环境、管理等海量数据存在多源异构特征使得安全风险评估不确定性增加。使用智能算法对空间生产场景进行模拟建模,对影响矿井安全的因素建立预警指标体系并对指标量化与预处理,通过BP神经网络模型对预处理后的指标数据模型训练与测试,测试结果表明,随着迭代次数的增加,模型的收敛性与准确率极大提高,可以最大限度地提供矿井安全风险评估决策所用信息、为提高煤矿安全监测的效率和监测深度提供技术支持。

数据挖掘技术在高校学生评教中的应用研究

文章从当前高校学生评教的现实情况入手,概括论述了与数据挖掘技术相关的一系列内容,诸如数据挖掘的定义、过程以及方式,进而分析了数据挖掘技术在高校学生评教中的优势与价值,并重点阐述了数据挖掘技术在高校学生评教系统中的具体应用。旨在进一步突出数据挖掘技术与高校教育教学工作的紧密联系度,同时证明数据挖掘技术在促进高校学生评教方式改革以及切实提高高校教育教学质量中所产生的深远影响。

基于数据挖掘的课程思政教学资源个性化推荐方法——以计算机类课程为例

思政教学资源是指用于开展思政教育的各类资源,为提高课程思政教学质量,现提出基于数据挖掘的课程思政教学资源个性化推荐方法。首先,以计算机类课程为例开展研究,构建计算机类课程思政教学资源推荐模型,分析学习行为与对应的思政教学资源。其次,基于数据挖掘提取计算机类课程中思政教学资源特征,为后续的教学资源推荐提供保障。最后,实现思政教学资源个性化智能推荐。实验结果表明:基于数据挖掘的课程思政教学资源个性化推荐方法的准确性明显优于传统方法,证明该方法在课程教学方法上具有一定可行性。

基于数据挖掘技术的医学检验技术线上教学效果评估系统设计

传统教学评估系统依赖人工或简单工具处理数据,难以深入分析海量数据,且易受个人偏见影响,评估结果不够准确公正。为优化医学检验技术线上教学评估效果,文章设计了基于数据挖掘技术的评估系统。在硬件方面,系统采用MSP430单片机与DS1302时钟芯片,确保实时性和准确性;在软件方面,构建评估结构,明确角色功能,建立数据仓库,细化数据结构表,满足查询需求。系统以赋分比和专业权重为依据生成评估报告,减少主观干扰,提升公正性和准确性。经测试,该系统性能卓越,具备实际应用价值。

工程教育认证背景下数据挖掘课程群的构建与实践研究

以工程教育认证为引领,根据数据挖掘分析在专业认证申请中制定的毕业生应该具备的知识和能力要求,以培养高质量数据分析、数据挖掘人才为宗旨,制定课程群素质、能力、知识三位一体的培养目标,结合学校应用型本科定位、专业培养目标及课程群培养目标构建课程目标能力点与毕业指标点关系结构体系,整合教学资源、建立课程群关联,创新实践教学体系,改革教学模式与方法、考核模式等,从而持续有效地提升学生的数据分析挖掘能力和综合素养,更好地达到行业对人才的认可标准。

基于改进SPRINT分类算法的数据挖掘模型

为解决目前数据挖掘模型分类时间长、挖掘准确率不高的问题,提出基于改进决策树分类算法(SPRINT)的数据挖掘模型。先采用最大-最小规范化公式完成原始数据线性变换,利用改进后的SPRINT分类算法按照输入数据特性进行分类,使用协同过滤技术生成与数据相近的属性集,计算数据属性相似度,生成语义规则集,为用户提供更优的数据服务。选取某公司营销数据集作为样本进行对比实验,结果表明,与对比模型相比,所提出的数据挖掘模型分类时间更短,挖掘准确率更高,能为用户提供更优质的数据服务。

基于数据库技术的计算机数据挖掘平台设计

数据库技术提供数据存储、查询等功能,数据挖掘技术则利用算法从数据中提取模式。基于数据库技术的计算机数据挖掘平台设计与实现,旨在融合两个领域的优点,开发出能够高效处理和分析大规模数据集的应用平台。文章介绍了基于数据库技术的计算机数据挖掘平台的设计与实现过程,探讨了计算机数据挖掘平台的具体设计,旨在提供高效可靠易用的数据挖掘平台。

数据挖掘技术在医院图书馆服务优化中的应用

为了提升医院图书馆的服务效率和信息化水平,文章设计并实现了一个基于数据挖掘技术的医院图书馆服务系统。该系统采用分层架构设计。其中,系统的资源采集层通过ETL技术有效采集医院相关文献资源;资源存储层运用决策树算法对采集的资源进行分类和存储;资源服务层通过访问接口为用户提供高效的服务支持;资源应用层利用数据挖掘技术优化检索和推荐机制,提高服务质量和效率。系统的测试结果表明,该系统能够显著提高医院图书馆文献资源的检索准确率,为医院图书馆的信息服务工作提供有力的支持。