检索结果-南通市图书馆

Enhancing Network Intrusion Detection Model Using Machine Learning Algorithms

Computers, Materials & Continua 2021年第4期67卷 979-990页

作者： nancy awadallah awad Department of Computer and Information Systems Sadat Academy for Management SciencesCairo11742Egypt

After the digital revolution,large quantities of data have been generated with time through various networks.The networks have made the process of data analysis very difficult by detecting attacks using suitable techniques.While Intrusion Detection Systems(IDSs)secure resources against threats,they still face challenges in improving detection accuracy,reducing false alarm rates,and detecting the unknown ones.This paper presents a framework to integrate data mining classification algorithms and association rules to implement network intrusion detection.Several experiments have been performed and evaluated to assess various machine learning classifiers based on the KDD99 intrusion dataset.Our study focuses on several data mining algorithms such as;naïve Bayes,decision trees,support vector machines,decision tables,k-nearest neighbor algorithms,and artificial neural networks.Moreover,this paper is concerned with the association process in creating attack rules to identify those in the network audit data,by utilizing a KDD99 dataset anomaly detection.The focus is on false negative and false positive performance metrics to enhance the detection rate of the intrusion detection system.The implemented experiments compare the results of each algorithm and demonstrate that the decision tree is the most powerful algorithm as it has the highest accuracy(0.992)and the lowest false positive rate(0.009).

关键词： Intrusion detection association rule data mining algorithms KDD99

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Analyzing Customer Reviews on Social Media via Applying Association Rule

引用

Computers, Materials & Continua 2021年第8期68卷 1519-1530页

作者： nancy awadallah awad Amena Mahmoud Department of Computer and Information Systems Sadat Academy for Management SciencesCairo11742Egypt Faculty of computers and Information Department of Computer ScienceKafr el Sheikh UniversityKafr El Sheikh33511Egypt

The rapid growth of the use of social media opens up new challenges and opportunities to analyze various aspects and patterns in communication.In-text mining,several techniques are available such as information clustering,extraction,summarization,classification.In this study,a text mining framework was presented which consists of 4 phases retrieving,processing,indexing,and mine association rule phase.It is applied by using the association rule mining technique to check the associated term with the Huawei P30 Pro phone.Customer reviews are extracted from many websites and Facebook groups,such as ***,CNET.Facebook and *** technology,where customers from all over the world placed their notes on cell phones.In this analysis,a total of 192 reviews of Huawei P30 Pro were collected to evaluate them by text mining techniques.The findings demonstrate that Huawei P30 Pro,has strong points such as the best safety,high-quality camera,battery that lasts more than 24 hours,and the processor is very fast.This paper aims to prove that text mining decreases human efforts by recognizing significant documents.This will lead to improving the awareness of customers to choose their products and at the same time sales managers also get to know what their products were accepted by customers suspended.

关键词： Machine learning text mining social media big data association rule document clustering

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Improving Reconstructed Image Quality via Hybrid Compression Techniques

引用

Computers, Materials & Continua 2021年第3期66卷 3151-3160页

作者： nancy awadallah awad Amena Mahmoud Department of Computer and Information Systems Sadat Academy for Management SciencesCairo11742Egypt Department of Computer Science Kafr el Sheikh University33511Egypt

Data compression is one of the core fields of study for applications of image and video processing.The raw data to be transmitted consumes large bandwidth and requires huge storage space as a result,it is desirable to represent the information in the data with considerably fewer bits by the mean of data compression techniques,the data must be reconstituted very similarly to the initial form.In this paper,a hybrid compression based on Discrete Cosine Transform(DCT),DiscreteWavelet Transform(DWT)is used to enhance the quality of the reconstructed image.These techniques are followed by entropy encoding such as Huffman coding to give additional compression.Huffman coding is optimal prefix code because of its implementation is more simple,faster,and easier than other codes.It needs less execution time and it is the shortest average length and the measurements for analysis are based upon Compression Ratio,Mean Square Error(MSE),and Peak Signal to Noise Ratio(PSNR).We applied a hybrid algorithm on(DWT–DCT 2×2,4×4,8×8,16×16,32×32)blocks.Finally,we show that by using a hybrid(DWT–DCT)compression technique,the PSNR is reconstructed for the image by using the proposed hybrid algorithm(DWT–DCT 8×8 block)is quite high than DCT.

关键词： Image compression discrete cosine transform PSNR discrete wavelet transform hybrid algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Using Semantic Web Technologies to Improve the Extract Transform Load Model

引用

Computers, Materials & Continua 2021年第8期68卷 2711-2726页

作者： Amena Mahmoud Mahmoud Y.Shams O.M.Elzeki nancy awadallah awad Department of Computer Science Kafrelshiekh UniversityKafrelshiekhEgypt Department of Machine Learning Kafrelsheikh UniversityKafrelshiekhEgypt Department of Computer Science Mansoura UniversityMansouraEgypt Department of Computer and Information Systems Sadat Academy for Management SciencesCairoEgypt

Semantic Web(SW)provides new opportunities for the study and application of big data,massive ranges of data sets in varied formats from multiple sources.Related studies focus on potential SW technologies for resolving big data problems,such as structurally and semantically heterogeneous data that result from the variety of data formats(structured,semi-structured,numeric,unstructured text data,email,video,audio,stock ticker).SW offers information semantically both for people and machines to retain the vast volume of data and provide a meaningful output of unstructured data.In the current research,we implement a new semantic Extract Transform Load(ETL)model that uses SW technologies for aggregating,integrating,and representing data as linked data.First,geospatial data resources are aggregated from the internet,and then a semantic ETL model is used to store the aggregated data in a semantic model after converting it to Resource Description Framework(RDF)format for successful integration and representation.The principal contribution of this research is the synthesis,aggregation,and semantic representation of geospatial data to solve problems.A case study of city data is used to illustrate the semantic ETL model’s functionalities.The results show that the proposed model solves the structural and semantic heterogeneity problems in diverse data sources for successful data aggregation,integration,and representation.

关键词： Semantic web big data ETL model linked data geospatial data

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：