Online intrusion detection systems play an important role in protecting IT systems. Tools like Sn... more Online intrusion detection systems play an important role in protecting IT systems. Tools like Snort, firewall also detect intrusions. Such intrusion detection systems provide feedback in the form of alerts. However, the number of alerts is more in number and often security personnel are confused with such voluminous messages. This makes them difficult to take decision immediately. They take time to analyze the alerts and come to a conclusion for directions for taking actions. The security risk estimation and resolving the security problem depends on quick understanding of alerts. The bulk of alerts given by low level intrusion detection systems make it time consuming to arrive at decisions. To overcome this problem the alerts provided by low level detection systems can be programmatically aggregated and summarized alerts can be given to security personnel so as to enable them to draw conclusions quickly and take required actions. We propose a new technique for the purpose of online...
Web is a collection of inter-related files on one or more Web servers. Web mining is one of the m... more Web is a collection of inter-related files on one or more Web servers. Web mining is one of the mining technologies, which applies data mining techniques in large amount of web data to improve the web services. Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. The Web Mining is an application of Data Mining. Without the internet, life would have been almost impossible. The data available on the web is so voluminous and heterogeneous that it becomes an essential factor to mine this available data to make it presentable, useful, and pertinent to a particular problem. Web mining deals with extracting these interesting patterns and developing useful abstracts from diversified sources. The present paper deals with a preliminary discussion of WEB mining, few key computer science contributions in the field of web mining and outlines some promising areas of future research.
Introduction Machine learning is a method of data analysis that automates analytical model buildi... more Introduction Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. Because of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It's a science that's not new – but one that's gaining fresh momentum. Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage. Traditional Business Accounting requires a degree of human intervention, which will be discarded by machine learning, since it continuously updates its learning, without being explicitly programmed to do so. With self-driving cars, and other smart devices, which assist humans, and even take over it completely, machine learning is certainly the next hot piece of cake in the market. All eyes are set on it on how it will impact business analytics. Realizing the potential of business analytics, many companies are seeking out to harness business analytics tools to help achieve a competitive edge. Machine learning is the cherry on the cake, which will help scan structured and unstructured data; and extract appropriate data to take correct decisions. Objective of the Book This book is intended to provide the information on the machine learning techniques that can be in business problems in efficient way. Moreover, it will encourage the data Scientists to take a proactive attitude toward applying machine learning techniques in business. Hence, publishing this book will be of interest to researchers, academics, students, and practitioners of data analytics.
Online intrusion detection systems play an important role in protecting IT systems. Tools like Sn... more Online intrusion detection systems play an important role in protecting IT systems. Tools like Snort, firewall also detect intrusions. Such intrusion detection systems provide feedback in the form of alerts. However, the number of alerts is more in number and often security personnel are confused with such voluminous messages. This makes them difficult to take decision immediately. They take time to analyze the alerts and come to a conclusion for directions for taking actions. The security risk estimation and resolving the security problem depends on quick understanding of alerts. The bulk of alerts given by low level intrusion detection systems make it time consuming to arrive at decisions. To overcome this problem the alerts provided by low level detection systems can be programmatically aggregated and summarized alerts can be given to security personnel so as to enable them to draw conclusions quickly and take required actions. We propose a new technique for the purpose of online...
Web is a collection of inter-related files on one or more Web servers. Web mining is one of the m... more Web is a collection of inter-related files on one or more Web servers. Web mining is one of the mining technologies, which applies data mining techniques in large amount of web data to improve the web services. Wide Web provides every internet citizen with access to an abundance of information, but it becomes increasingly difficult to identify the relevant pieces of information. Research in web mining tries to address this problem by applying techniques from data mining and machine learning to Web data and documents. The Web Mining is an application of Data Mining. Without the internet, life would have been almost impossible. The data available on the web is so voluminous and heterogeneous that it becomes an essential factor to mine this available data to make it presentable, useful, and pertinent to a particular problem. Web mining deals with extracting these interesting patterns and developing useful abstracts from diversified sources. The present paper deals with a preliminary discussion of WEB mining, few key computer science contributions in the field of web mining and outlines some promising areas of future research.
Introduction Machine learning is a method of data analysis that automates analytical model buildi... more Introduction Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. Because of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It's a science that's not new – but one that's gaining fresh momentum. Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage. Traditional Business Accounting requires a degree of human intervention, which will be discarded by machine learning, since it continuously updates its learning, without being explicitly programmed to do so. With self-driving cars, and other smart devices, which assist humans, and even take over it completely, machine learning is certainly the next hot piece of cake in the market. All eyes are set on it on how it will impact business analytics. Realizing the potential of business analytics, many companies are seeking out to harness business analytics tools to help achieve a competitive edge. Machine learning is the cherry on the cake, which will help scan structured and unstructured data; and extract appropriate data to take correct decisions. Objective of the Book This book is intended to provide the information on the machine learning techniques that can be in business problems in efficient way. Moreover, it will encourage the data Scientists to take a proactive attitude toward applying machine learning techniques in business. Hence, publishing this book will be of interest to researchers, academics, students, and practitioners of data analytics.
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