[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117600-en":3,"doc-seo-117600-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117600,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",6,"Technology","Dynamic Filtering of Malicious Records Using Machine Learning Integrated Databases - Slideshare","Machine learning, deep learning, and predictive analytics underpin research across engineering, finance, economics, and real-time imaging, enabling more accurate solutions to real-world problems. The presentation reviews common research tools and open-source or custom frameworks and highlights large-scale adoption in government and social services to reduce error. It also surveys major industry contributors and positions knowledge discovery and predictive analytics as core drivers for malicious-record filtering approaches.","Dynamic filtering of malicious records using machine learning  \nintegrated databases  \nAhmed Abbood Ali1, Ahmed Raee AL-Mhanawi2, Aqeel Kamil Kadhim3  \n1Directorate General of Education Baghdad-Alkarkh-1  \n2Directorate General of Education AL-Qadisiyah  \n3Al-Imam Al-Kadhum University College for Islamic Science  \n\n| ABSTRACT |\n| --- |\n| Machine Learning, Deep Learning and Predictive Analytics are the key domains of research in assorted domains of implementations including engineering, finance, economics, real time imaging and many others. The researchers are working on different tools and technologies including open source and own developed frameworks so that the higher degree of accuracy can be achieved. The research reports from Market Research News US predicted that the global market size of machine learning based implementations will exceed 20 billion dollars in year 2024. Most of the government and social services are nowadays in process to be deployed with the advanced technologies of machine learning and deep learning so that the minimum error factor can be there. The key players in the industry include; Google, Facebook, IBM Watson, Baidu, Apple, Microsoft, Wipro, Amazon, Intel, Nuance and many others which are working on the advanced algorithms and implementation perspectives of machine learning. |\n| Keywords: Machine Learning, Malware Analysis, Knowledge Discovery |\n| Corresponding Author:\u003Cbr>Ahmed Abbood Ali\u003Cbr>Departement, 1Directorate General of Education Baghdad University \\#\u003Cbr>Address, Bghdad , Iraq\u003Cbr>[E-mail: ](E-mail: ahmed_swe.@yahoo.com)[ahmed_swe.@yahoo.com](E-mail: ahmed_swe.@yahoo.com) |\n\n1. Introduction  \nThe domain of knowledge discovery and predictive analytics is more focused and dependent towards machine learning and deep learning-based applications. Enormous algorithms and methodologies are available in machine learning for scientific applications and solutions for real world problems [1] . Broadly, there are three types of approaches in the machine learning which are widely integrated for the problem solving and predictive mining. These approaches include; supervised learning, unsupervised learning and reinforced learning [2, 3] . These approaches are used as per the specific domain of implementation and accuracy required. The industry of deep learning is very closely associated with machine learning to integrate the higher degree of performance and accuracy with the minimum error rate [4, 5] . The classical applications of machine learning include the following perspectives of Computer Vision and Graphics, Engineering Optimization, Biomedical and Bio-Informatics, Software Engineering and Internet Frauds Detection, Customer Relationship Management, Time Series Forecasting, Data mining and Predictive Mining, Chemical Informatics, Web and Mail filtering, Wireless Network Analytics, Adaptive Web Applications and Analysis, Natural language processing (NLP), Automatic taxonomy construction, Automatic summarization, Grammar Evaluations, Language Analytics, Speech recognition, Handwriting recognition, Optical character recognition, Speech Processing synthesis, Sentiment Data Analysis, Machine Process Automation and translation, Query Execution and Processing, Text mining and simplification, Information Retrieval and Predictive Mining,  \nPattern recognition, Optical character recognition, Image recognition, Facial recognition system, Handwriting recognition, Speech recognition, Recommendation system, Content-based filtering, Collaborative filtering, ECommerce, Hybrid recommender systems, Search engine Optimization, Robot Locomotion, Social Engineering and many others [6, 7, 8] .  \n2. Results  \nPredictive Analysis on Malicious Records  \nFollowing are the prominent tools and software, libraries used for the machine learning and data science-based implementations [9,10] .  \nTable 1. Machine Learning Libraries and Toolkits  \n\n| CNTK | Apache SystemML | Caffe |\n| --- | --- | --- |\n| Deeplearning4j | ELKI | GN","cbCaimnK4aAOsG9z","https://ap.wps.com/l/cbCaimnK4aAOsG9z","pdf",576049,1,8,"English","en",105,"# Introduction\n## Machine learning approaches\n## Deep learning and performance\n# Results\n## Predictive analysis on malicious records\n## Machine learning libraries and toolkits\n## Classifier-based prediction with Weka\n## J48 classifier example","[{\"question\":\"What main research domains does the document emphasize?\",\"answer\":\"Machine learning, deep learning, and predictive analytics are presented as the key domains. They are positioned as enabling technologies for high-accuracy predictive and knowledge discovery tasks.\"},{\"question\":\"Which types of machine learning approaches are discussed?\",\"answer\":\"The document outlines supervised learning, unsupervised learning, and reinforced learning. These are selected based on the implementation domain and the required accuracy.\"},{\"question\":\"How is malicious record classification demonstrated in the Weka example?\",\"answer\":\"A network-traffic dataset (Malicious_Traffic_Records.arff) is used to train a classifier, and a separate test dataset predicts the class. The solution integrates the J48 classifier to determine classes based on the traffic sequence parameters.\"}]","Dynamic Filtering of Malicious Records Using Machine Learning Integrated Databases - Slideshare | PDF",1785677205,20,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"dynamic-filtering-of-malicious-records-using-machine-learning-integrated-databases-slideshare","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/dynamic-filtering-of-malicious-records-using-machine-learning-integrated-databases-slideshare/117600/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What main research domains does the document emphasize?","Question",{"text":75,"@type":76},"Machine learning, deep learning, and predictive analytics are presented as the key domains. 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