WIND: A warehouse for internet data

Faulstich, Lukas; Spiliopoulou, Myra; Linnemann, Volker

doi:10.1007/3-540-63263-8_20

Cited by 8 publications

(5 citation statements)

References 10 publications

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“…Different Slaves can operate at the same time rendering more efficient, reducing the answer times and avoiding simultaneous accesses to the same resources [39]. Slaves call Scribes [28,29,30,31,32,33]. Scribes receive Web pages crawled from Slaves.…”

Section: A Service Oriented Web Mining Architecturementioning

confidence: 99%

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A Decision Support System base line Flexible Architecture to Intrusion Detection

Castellano¹,

Marra²,

Aprile³

et al. 2007

JSW

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Becoming more competitive and more effective in the current scenes of Business and Public Administration, the organizations must be able to approach easily and quickly to the information on the customers and the external conditions of market. In other words it means to head at the improvement of the Decision Support Systems. Decision Support System is concerned with developing systems aimed at helping decision makers solve problems and make decisions. In this paper, we refer to a decision support system based on flexible architecture able to discover the knowledge in a distributed and heterogeneous multi-organization environment. The system architecture has been designed according to the Service Oriented Architecture and Model View Controller design pattern. Moreover it is based on a mining engine whose purpose is to generate and to use suitable e-services for knowledge by driving the user through various stages of the Knowledge Discovery process. An Intrusion Detection application is also described.

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Section: A Service Oriented Web Mining Architecturementioning

confidence: 99%

“…This framework consists of one of these techniques as well as a support environment that enables system builders to interactively and iteratively drive the process of constructing and evaluating detection models. The end product is concise and intuitive classification rules that can detect intrusions [29].…”

Section: A Defining Miners For Intrusion Detectionmentioning

confidence: 99%

A Decision Support System base line Flexible Architecture to Intrusion Detection

Castellano¹,

Marra²,

Aprile³

et al. 2007

JSW

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“…Furthermore, in order to support high-level decision-making, users need to comprehensively utilize and analyze the data from various sources [8]. This also motivates the creation of web warehouses, which are data warehouses that contain consolidated data obtained from web sources [9,10].…”

Section: Introductionmentioning

confidence: 99%

Web warehouse – a new web information fusion tool for web mining

Wei

Wang

et al. 2008

Information Fusion

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“…On the one hand, we may try to define a reference model intended to streamline the design and implementation of the web information systems, hence, standardizing information access in the web. Faulstich et al (1997), Scharl (1999), Carchiolo et al (2000), and Kohonen et al (2000) are various examples of such an approach. However, since the web is in essence a semi-structured and decentralized environment, globalization of any reference model requires a lot of effort, if it is not simply impossible.…”

Section: Introductionmentioning

confidence: 99%

Efficient and Anonymous Web-Usage Mining for Web Personalization

Shahabi

Banaei-Kashani

2003

INFORMS Journal on Computing

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The world-wide web (WWW) is the largest distributed information space and has grown to encompass diverse information resources. Although the web is growing exponentially, the individual's capacity to read and digest content is essentially fixed. The full economic potential of the web will not be realized unless enabling technologies are provided to facilitate access to web resources. Currently web personalization is the most promising approach to remedy this problem, and web mining, particularly web-usage mining, is considered a crucial component of any efficacious web-personalization system. In this paper, we describe a complete framework for web-usage mining to satisfy the challenging requirements of webpersonalization applications. For on-line and anonymous web personalization to be effective, web usage mining must be accomplished in real time as accurately as possible. On the other hand, web-usage mining should allow a compromise between scalability and accuracy to be applicable to real-life websites with numerous visitors. Within our web-usage-mining framework, we introduce a distributed user-tracking approach for accurate, scalable, and implicit collection of the usage data. We also propose a new model, the feature-matrices (FM) model, to discover and interpret users' access patterns. With FM, various spatial and temporal features of usage data can be captured with flexible precision so that we can trade off accuracy for scalability based on the specific application requirements. Moreover, tunable complexity of the FM model allows real-time and adaptive access pattern discovery from usage data. We define a novel similarity measure based on FM that is specifically designed for accurate classification of partial navigation patterns in real time. Our extensive experiments with both synthetic and real data verify correctness and efficacy of our webusage-mining framework for anonymous and efficient web personalization.

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WIND: A warehouse for internet data

Cited by 8 publications

References 10 publications

A Decision Support System base line Flexible Architecture to Intrusion Detection

A Decision Support System base line Flexible Architecture to Intrusion Detection

Web warehouse – a new web information fusion tool for web mining

Efficient and Anonymous Web-Usage Mining for Web Personalization

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