Data model for warehousing historical Web information |
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| Affiliation: | 1. Department of Medical Biotechnology, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran;2. Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran;3. Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran;4. Department of Clinical Biochemistry and Laboratory Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran;5. Molecular Targeting Therapy Research Group, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran;6. Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran;1. Department of Information Systems, W.P. Carey School of Business, Arizona State University, United States;2. Department of Mathematics and Statistics, Hang Seng Management College, Hong Kong, China;3. School of Information Systems, Singapore Management University, Singapore |
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| Abstract: | In this paper, we present a temporal web data model designed for warehousing historical data from World Wide Web (WWW). As the Web is now populated with large volume of information, it has become necessary to capture selected portions of web information in a data warehouse that supports further information processing such as data extraction, data classification, and data mining. Nevertheless, due to the unstructured and dynamic nature of Web, the traditional relational model and its temporal variants could not be used to build such a data warehouse. In this paper, we therefore propose a temporal web data model that represents web documents and their connectivities in the form of temporal web tables. To represent web data that evolve with time, a visible time interval is associated with each web document. To manipulate temporal web tables, we have defined a set of web operators with capabilities ranging from extracting WWW information into web tables, to merging information from different web tables. We further illustrate the use of our temporal web data model using some realistic motivating examples. |
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