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The successful website must take care of issues related to user satisfaction and security of website. This may be in terms of easiness of user access to contents of website or quick traversal through the website. Website administr...
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The successful website must take care of issues related to user satisfaction and security of website. This may be in terms of easiness of user access to contents of website or quick traversal through the website. Website administrator concerns about security and integrity of the website. The behavior of the website at the peak time of operations is the real test for the site administrator. This key information can be obtained by analysis of server log data of the website. The analysis of weblog data is the key to the success of any website. It gives the insight to activities of visitors and provides a way to the improvement of the website for better performance. The analysis of weblog data also provides valuable information for website security and development.
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The expansion of the World Wide Web (Web for short) has resulted in a large amount of data that is now in general freely available for user access. The different types of data have to be managed and organized in such a way that th...
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The expansion of the World Wide Web (Web for short) has resulted in a large amount of data that is now in general freely available for user access. The different types of data have to be managed and organized in such a way that they can be accessed by different users efficiently. Therefore, the application of data mining techniques on the Web is now the focus of an increasing number of researchers. Clustering is one of the various type of methods that can be applied on Web data in order to provide more dynamic and user friendly Web-based service. Because the amount of data stored in such Web systems is great in this case the data mining aspects of clustering should be used. This paper deals with the different aspects of Web data mining and provides an overview about the various techniques used in this field.
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摘要 :
The successful website must take care of issues related to user satisfaction and security of website. This may be in terms of easiness of user access to contents of website or quick traversal through the website. Website administr...
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The successful website must take care of issues related to user satisfaction and security of website. This may be in terms of easiness of user access to contents of website or quick traversal through the website. Website administrator concerns about security and integrity of the website. The behavior of the website at the peak time of operations is the real test for the site administrator. This key information can be obtained by analysis of server log data of the website. The analysis of weblog data is the key to the success of any website. It gives the insight to activities of visitors and provides a way to the improvement of the website for better performance. The analysis of weblog data also provides valuable information for website security and development.
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摘要 :
The reason at the back of data overloading dilemma faced by internet users on internet includes: excessive web information and billions of users around worldwide. Because of this, providing the internet users with more intended da...
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The reason at the back of data overloading dilemma faced by internet users on internet includes: excessive web information and billions of users around worldwide. Because of this, providing the internet users with more intended data is a challenging task in web applications. The lotsof information available on internet are a fertile field for applying data mining techniques. This is what we call Web Mining (WM). The research in WM deals with research from many fields like database, Artificial Intelligence (machine learning [supervised, semi supervised, unsupervised andreinforcement], neural network and natural language processing (NLP)) and information retrieval. Here, research related to web mining and their categories is highlighted. We also situate comparison of most popular algorithms used from the field of data mining in pattern discovery phase ofthe WM.
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The purpose of this paper is to provide a more current evaluation and update of web mining research and techniques available. Current advances in each of the three different types of web mining are reviewed in the categories of we...
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The purpose of this paper is to provide a more current evaluation and update of web mining research and techniques available. Current advances in each of the three different types of web mining are reviewed in the categories of web content mining, web usage mining, and web structure mining. For each tabulated research work, we examine such key issues as web mining process, methods/techniques, applications, data sources, and software used. Unlike previous investigators, we divide web mining processes into the following five subtasks: (1) resource finding and retrieving, (2) information selection and preprocessing, (3) patterns analysis and recognition, (4) validation and interpretation, and (5) visualization. This paper also reports the comparisons and summaries of selected software for web mining. The web mining software selected for discussion and comparison in this paper are SPSS Clementine, Megaputer PolyAnalyst, ClickTracks by web analytics, and QL2 by QL2 Software Inc. Applications of these selected web mining software to available data sets are discussed together with abundant presentations of screen shots, as well as conclusions and future directions of the research.
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Web usage mining is the branch of web mining that deals with mining of data over the web. Web mining can be categorized as web content mining, web structure mining, web usage mining. In this paper, we have summarized the web usage...
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Web usage mining is the branch of web mining that deals with mining of data over the web. Web mining can be categorized as web content mining, web structure mining, web usage mining. In this paper, we have summarized the web usage mining results executed over the user tool WMOT (web mining optimized tool) based on the WEKA tool that has been used to apply various classification algorithms such as Naive Bayes, KNN, SVM and tree based algorithms. Authors summarized the results of classification algorithms on WMOT tool and compared the results on the basis of classified instances and identify the algorithms that gives better instances accuracy.
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摘要 :
Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large...
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Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large databases. Application of data mining techniques to the World Wide Web is referred as web data mining. World Wide Web is a huge data repository and is growing with the explosive rate of about 1 million pages a day. Each access to the web page is recorded in a file called Web logs. As the information available on World Wide Web is growing the access to the web sites is also growing. That makes web logs a huge repository of web usage data. These web logs, when mined properly can provide useful information for decision-making. As web logs keep the usage detail, mining the web log is referred as web usage mining. The designer of the web site, analyst and management executives are interested in extracting this hidden information from web logs for decision making. Hence, discovery and analysis of useful information from the Web logs is a practical necessity of today. We review in this paper, web usage mining process and the area where researchers are focusing now a day.
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摘要 :
Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large...
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Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large databases. Application of data mining techniques to the World Wide Web is referred as web data mining. World Wide Web is a huge data repository and is growing with the explosive rate of about 1 million pages a day. Each access to the web page is recorded in a file called Web logs. As the information available on World Wide Web is growing the access to the web sites is also growing. That makes web logs a huge repository of web usage data. These web logs, when mined properly can provide useful information for decision-making. As web logs keep the usage detail, mining the web log is referred as web usage mining. The designer of the web site, analyst and management executives are interested in extracting this hidden information from web logs for decision making. Hence, discovery and analysis of useful information from the Web logs is a practical necessity of today. We review in this paper, web usage mining process and the area where researchers are focusing now a day.
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摘要 :
Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large...
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Data Mining is a research discipline involving the study of techniques to search for patterns in large collections of data. It is the process of automatic extraction of implicit, novel, useful, and understandable patterns in large databases. Application of data mining techniques to the World Wide Web is referred as web data mining. World Wide Web is a huge data repository and is growing with the explosive rate of about 1 million pages a day. Each access to the web page is recorded in a file called Web logs. As the information available on World Wide Web is growing the access to the web sites is also growing. That makes web logs a huge repository of web usage data. These web logs, when mined properly can provide useful information for decision-making. As web logs keep the usage detail, mining the web log is referred as web usage mining. The designer of the web site, analyst and management executives are interested in extracting this hidden information from web logs for decision making. Hence, discovery and analysis of useful information from the Web logs is a practical necessity of today. We review in this paper, web usage mining process and the area where researchers are focusing now a day.
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We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in th...
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We combine the web usage mining and fuzzy clustering and give the concept of web fuzzy clustering, and then put forward the web fuzzy clustering processing model which is discussed in detail. Web fuzzy clustering can be used in the web users clustering and web pages clustering, In the end, a case study is given and the result has proved the feasibility of using web fuzzy clustering in web pages clustering.
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