Latifur Khan – författare & böcker

Design and Implementation of Data Mining Tools

AvBhavani Thuraisingham,Latifur Khanm. fl.

Häftad, Engelska, 2019

908 kr

Skickas inom 10-15 vardagar

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors’ own research work, the book takes a practical approach to the subject.The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification. Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.

Secure Data Science

Integrating Cyber Security and Data Science

AvBhavani Thuraisingham,Murat Kantarcioglum. fl.

Inbunden, Engelska, 2022

1 750 kr

Skickas inom 10-15 vardagar

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science.After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media.This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Big Data Analytics with Applications in Insider Threat Detection

AvBhavani Thuraisingham,Pallabi Parveenm. fl.

Häftad, Engelska, 2020

704 kr

Skickas inom 10-15 vardagar

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Bhavani Thuraisingham, Satyen Abrol, Raymond Heatherly, Murat Kantarcioglu, Vaibhav Khadilkar, Latifur Khan - Analyzing and Securing Social Networks, Häftad

Analyzing and Securing Social Networks

AvBhavani Thuraisingham,Satyen Abrolm. fl.

Häftad, Engelska, 2020

704 kr

Skickas inom 10-15 vardagar

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants.The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided.The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.

Secure Data Science

Integrating Cyber Security and Data Science

AvLatifur Khan,Murat Kantarcioglum. fl.

E-bok

PDF, Engelska, 2022

774 kr

Läs direkt efter köp

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science.

After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media.

This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Secure Data Science

Integrating Cyber Security and Data Science

AvLatifur Khan,Murat Kantarcioglum. fl.

E-bok

Engelska, 2022

774 kr

Läs direkt efter köp

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science.

After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media.

This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Secure Data Science

Integrating Cyber Security and Data Science

AvBhavani Thuraisingham,Murat Kantarcioglum. fl.

Häftad, Engelska, 2024

672 kr

Skickas inom 10-15 vardagar

Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science.After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media.This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Latifur Khan, Vaibhav Khadilkar, Murat Kantarcioglu, Raymond Heatherly, Satyen Abrol, Bhavani Thuraisingham - Analyzing and Securing Social Networks, E-bok

Analyzing and Securing Social Networks

AvLatifur Khan,Vaibhav Khadilkarm. fl.

E-bok

Engelska, 2016

675 kr

Läs direkt efter köp

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technolo

Design and Implementation of Data Mining Tools

AvBhavani Thuraisingham,Latifur Khanm. fl.

E-bok

Engelska, 2009

1 074 kr

Läs direkt efter köp

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject.The first part of the boo

Big Data Analytics with Applications in Insider Threat Detection

AvLatifur Khan,Mohammad Mehedy Masudm. fl.

E-bok

Engelska, 2017

831 kr

Läs direkt efter köp

Today''s malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Design and Implementation of Data Mining Tools

AvBhavani Thuraisingham,Latifur Khanm. fl.

Inbunden, Engelska, 2009

1 525 kr

Skickas inom 10-15 vardagar

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors’ own research work, the book takes a practical approach to the subject.The first part of the book reviews data mining techniques, such as artificial neural networks and support vector machines, as well as data mining applications. The second section covers the design and implementation of data mining tools for intrusion detection. It examines various designs and performance results, along with the strengths and weaknesses of the approaches. The third part presents techniques to solve the WWW prediction problem. The final part describes models that the authors have developed for image classification. Showing step by step how data mining tools are developed, this hands-on guide discusses the performance results, limitations, and unique contributions of data mining systems. It provides essential information for technologists to decide on the tools to select for a particular application, for developers to focus on alternative designs if an approach is unsuitable, and for managers to choose whether to proceed with a data mining project.

Design and Implementation of Data Mining Tools

AvBhavani Thuraisingham,Latifur Khanm. fl.

E-bok

PDF, Engelska, 2009

1 074 kr

Läs direkt efter köp

Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject.The first part of the boo

Data Mining Tools for Malware Detection

AvMehedy Masud,Latifur Khanm. fl.

Inbunden, Engelska, 2011

2 031 kr

Skickas inom 10-15 vardagar

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets. The authors describe the systems they have designed and developed: email worm detection using data mining, a scalable multi-level feature extraction technique to detect malicious executables, detecting remote exploits using data mining, and flow-based identification of botnet traffic by mining multiple log files. For each of these tools, they detail the system architecture, algorithms, performance results, and limitations. Discusses data mining for emerging applications, including adaptable malware detection, insider threat detection, firewall policy analysis, and real-time data miningIncludes four appendices that provide a firm foundation in data management, secure systems, and the semantic webDescribes the authors’ tools for stream data miningFrom algorithms to experimental results, this is one of the few books that will be equally valuable to those in industry, government, and academia. It will help technologists decide which tools to select for specific applications, managers will learn how to determine whether or not to proceed with a data mining project, and developers will find innovative alternative designs for a range of applications.

Data Mining Tools for Malware Detection

AvMehedy Masud,Latifur Khanm. fl.

E-bok

PDF, Engelska, 2016

1 921 kr

Läs direkt efter köp

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets. The authors describe the systems they have designed and developed: email worm detection using data mining, a scalable multi-level feature extraction technique to detect malicious executables, detecting remote exploits using data mining, and flow-based identification of botnet traffic by mining multiple log files. For each of these tools, they detail the system architecture, algorithms, performance results, and limitations. Discusses data mining for emerging applications, including adaptable malware detection, insider threat detection, firewall policy analysis, and real-time data miningIncludes four appendices that provide a firm foundation in data management, secure systems, and the semantic webDescribes the authors’ tools for stream data mining From algorithms to experimental results, this is one of the few books that will be equally valuable to those in industry, government, and academia. It will help technologists decide which tools to select for specific applications, managers will learn how to determine whether or not to proceed with a data mining project, and developers will find innovative alternative designs for a range of applications.

Multimedia Data Mining and Knowledge Discovery

AvValery A. Petrushin,Latifur Khan

Häftad, Engelska, 2014

2 008 kr

Skickas inom 10-15 vardagar

This tightly-edited collection of papers from leading researchers worldwide provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field.Written with graduates in mind, this much needed comprehensive reflection of the current state of multimedia data mining and knowledge discovery will also be a valuable resource for researchers in the field.This book provides an overview of the current state of the art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.Topics and Features: - Features a comprehensive introduction to multimedia data mining and its relevance today; - presents a global perspective of the field and its various components; - provides broad, yet thorough and detailed coverage of the subject; - numerous chapters reference websites with supplementary materials and demonstrations; - explores multimedia data exploration, multimedia data modeling and evaluation, and visualization; - offers an entire part devoted to applications and case studies.Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.

Data Mining Tools for Malware Detection

AvMehedy Masud,Latifur Khanm. fl.

E-bok

Engelska, 2016

1 921 kr

Läs direkt efter köp

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets. The authors describe the systems they have designed and developed: email worm detection using data mining, a scalable multi-level feature extraction technique to detect malicious executables, detecting remote exploits using data mining, and flow-based identification of botnet traffic by mining multiple log files. For each of these tools, they detail the system architecture, algorithms, performance results, and limitations. Discusses data mining for emerging applications, including adaptable malware detection, insider threat detection, firewall policy analysis, and real-time data miningIncludes four appendices that provide a firm foundation in data management, secure systems, and the semantic webDescribes the authors’ tools for stream data mining From algorithms to experimental results, this is one of the few books that will be equally valuable to those in industry, government, and academia. It will help technologists decide which tools to select for specific applications, managers will learn how to determine whether or not to proceed with a data mining project, and developers will find innovative alternative designs for a range of applications.

Analyzing and Securing Social Networks

AvBhavani Thuraisingham,Satyen Abrolm. fl.

Inbunden, Engelska, 2016

1 950 kr

Skickas inom 5-8 vardagar

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technologies that ensure the privacy of the participants of the network as well as provide controlled access to the information posted and exchanged by the participants.The authors explore security and privacy issues for social media systems, analyze such systems, and discuss prototypes they have developed for social media systems whose data are represented using semantic web technologies. These experimental systems have been developed at The University of Texas at Dallas. The material in this book, together with the numerous references listed in each chapter, have been used for a graduate-level course at The University of Texas at Dallas on analyzing and securing social media. Several experimental systems developed by graduate students are also provided.The book is divided into nine main sections: (1) supporting technologies, (2) basics of analyzing and securing social networks, (3) the authors’ design and implementation of various social network analytics tools, (4) privacy aspects of social networks, (5) access control and inference control for social networks, (6) experimental systems designed or developed by the authors on analyzing and securing social networks, (7) social media application systems developed by the authors, (8) secure social media systems developed by the authors, and (9) some of the authors’ exploratory work and further directions.

Analyzing and Securing Social Networks

AvLatifur Khan,Vaibhav Khadilkarm. fl.

E-bok

PDF, Engelska, 2016

675 kr

Läs direkt efter köp

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technolo

Big Data Analytics with Applications in Insider Threat Detection

AvBhavani Thuraisingham,Pallabi Parveenm. fl.

Inbunden, Engelska, 2017

1 670 kr

Skickas inom 10-15 vardagar

Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Big Data Analytics with Applications in Insider Threat Detection

AvLatifur Khan,Mohammad Mehedy Masudm. fl.

E-bok

PDF, Engelska, 2017

831 kr

Läs direkt efter köp

Today''s malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Multimedia Data Mining and Knowledge Discovery

AvValery A. Petrushin,Latifur Khan

Inbunden, Engelska, 2006

2 016 kr

Skickas inom 10-15 vardagar

This tightly-edited collection of papers from leading researchers worldwide provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field.Written with graduates in mind, this much needed comprehensive reflection of the current state of multimedia data mining and knowledge discovery will also be a valuable resource for researchers in the field.This book provides an overview of the current state of the art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.Topics and Features: - Features a comprehensive introduction to multimedia data mining and its relevance today; - presents a global perspective of the field and its various components; - provides broad, yet thorough and detailed coverage of the subject; - numerous chapters reference websites with supplementary materials and demonstrations; - explores multimedia data exploration, multimedia data modeling and evaluation, and visualization; - offers an entire part devoted to applications and case studies.Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.

Multimedia Data Mining and Knowledge Discovery

AvLatifur Khan,Valery A. Petrushin

E-bok

PDF, Engelska, 2007

2 508 kr

Läs direkt efter köp

This tightly-edited collection of papers from leading researchers worldwide provides an overview of the current state-of-the-art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.

Consisting of an introductory section and four topical parts, the book describes the objectives and current tendencies in multimedia data mining research and their applications. Each part contains an overview of its chapters and leads the reader with a structured approach through the diverse subjects in the field.

Written with graduates in mind, this much needed comprehensive reflection of the current state of multimedia data mining and knowledge discovery will also be a valuable resource for researchers in the field.

This book provides an overview of the current state of the art in the field of multimedia data mining and knowledge discovery, and discusses the variety of hot topics in multimedia data mining research.

Topics and Features: - Features a comprehensive introduction to multimedia data mining and its relevance today; - presents a global perspective of the field and its various components; - provides broad, yet thorough and detailed coverage of the subject; - numerous chapters reference websites with supplementary materials and demonstrations; - explores multimedia data exploration, multimedia data modeling and evaluation, and visualization; - offers an entire part devoted to applications and case studies.

Written with graduate students in mind, this much needed comprehensive survey of the current state of multimedia data mining and knowledge discovery will also serve as a valuable resource for researchers with interests in multimedia data mining, summarization, indexing, and retrieval.

Del 9652 - Lecture Notes in Computer Science

Advances in Knowledge Discovery and Data Mining

20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II

AvJames Bailey,Latifur Khanm. fl.

Häftad, Engelska, 2016

565 kr

Skickas inom 10-15 vardagar

This two-volume set, LNAI 9651 and 9652, constitutes thethoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advancesin Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, NewZealand, in April 2016.The 91 full papers were carefully reviewed andselected from 307 submissions. They are organized in topical sections named:classification; machine learning; applications; novel methods and algorithms;opinion mining and sentiment analysis; clustering; feature extraction andpattern mining; graph and network data; spatiotemporal and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems.

Advances in Knowledge Discovery and Data Mining

20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part II

AvRuili Wang,Joshua Zhexue Huangm. fl.

E-bok

PDF, Engelska, 2016

708 kr

Läs direkt efter köp

This two-volume set, LNAI 9651 and 9652, constitutes thethoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advancesin Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, NewZealand, in April 2016.

The 91 full papers were carefully reviewed andselected from 307 submissions. They are organized in topical sections named:classification; machine learning; applications; novel methods and algorithms;opinion mining and sentiment analysis; clustering; feature extraction andpattern mining; graph and network data; spatiotemporal and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems.

Del 9651 - Lecture Notes in Computer Science

Advances in Knowledge Discovery and Data Mining

20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I

AvJames Bailey,Latifur Khanm. fl.

Häftad, Engelska, 2016

565 kr

Skickas inom 10-15 vardagar

This two-volume set, LNAI 9651 and 9652, constitutes thethoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advancesin Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, NewZealand, in April 2016.The 91 full papers were carefully reviewed andselected from 307 submissions. They are organized in topical sections named:classification; machine learning; applications; novel methods and algorithms;opinion mining and sentiment analysis; clustering; feature extraction andpattern mining; graph and network data; spatiotemporal and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems.

Advances in Knowledge Discovery and Data Mining

20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I

AvRuili Wang,Joshua Zhexue Huangm. fl.

E-bok

PDF, Engelska, 2016

708 kr

Läs direkt efter köp

This two-volume set, LNAI 9651 and 9652, constitutes thethoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advancesin Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, NewZealand, in April 2016.

The 91 full papers were carefully reviewed andselected from 307 submissions. They are organized in topical sections named:classification; machine learning; applications; novel methods and algorithms;opinion mining and sentiment analysis; clustering; feature extraction andpattern mining; graph and network data; spatiotemporal and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems.

Del 10968 - Lecture Notes in Computer Science

Big Data – BigData 2018

7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings

AvFrancis Y. L. Chin,C. L. Philip Chenm. fl.

Häftad, Engelska, 2018

566 kr

Skickas inom 10-15 vardagar

This volume constitutes the proceedings of the 7th International Conference on BIGDATA 2018, held as Part of SCF 2018 in Seattle, WA, USA in June 2018.The 22 full papers together with 10 short papers published in this volume were carefully reviewed and selected from 97 submissions. They are organized in topical sections such as Data analysis, data as a service, services computing, data conversion, data storage, data centers, dataflow architectures, data compression, data exchange, data modeling, databases, and data management.

Big Data - BigData 2018

7th International Congress, Held as Part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018, Proceedings

AvLiang-Jie Zhang,Kisung Leem. fl.

E-bok

Engelska, 2018

734 kr

Läs direkt efter köp

This volume constitutes the proceedings of the 7th International Conference on BIGDATA 2018, held as Part of SCF 2018 in Seattle, WA, USA in June 2018.The 22 full papers together with 10 short papers published in this volume were carefully reviewed and selected from 97 submissions. They are organized in topical sections such as Data analysis, data as a service, services computing, data conversion, data storage, data centers, dataflow architectures, data compression, data exchange, data modeling, databases, and data management.

Företag, bibliotek eller offentlig verksamhet?

Latifur Khan – författare

Design and Implementation of Data Mining Tools

Secure Data Science

Big Data Analytics with Applications in Insider Threat Detection

Analyzing and Securing Social Networks

Secure Data Science

Secure Data Science

Secure Data Science

Analyzing and Securing Social Networks

Design and Implementation of Data Mining Tools

Big Data Analytics with Applications in Insider Threat Detection

Design and Implementation of Data Mining Tools

Design and Implementation of Data Mining Tools

Data Mining Tools for Malware Detection

Data Mining Tools for Malware Detection

Multimedia Data Mining and Knowledge Discovery

Data Mining Tools for Malware Detection

Analyzing and Securing Social Networks

Analyzing and Securing Social Networks

Big Data Analytics with Applications in Insider Threat Detection

Big Data Analytics with Applications in Insider Threat Detection

Multimedia Data Mining and Knowledge Discovery

Multimedia Data Mining and Knowledge Discovery

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Big Data – BigData 2018

Big Data - BigData 2018

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Om Bokus

Om Bokus

Populärt

Populärt

Inspiration

Inspiration