ESTIMATING MISSING VALUES OF SKYLINES IN INCOMPLETE DATABASE
作者： Nur Izura Udzir , Hamidah Ibrahim , Fatimah Sidi , Ali A. Alwan
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摘要: Incompleteness of data is a common problem in many databases including web heterogonous databases, multirelational spatial and temporal integration. The incompleteness introduces challenges processing queries as providing accurate results that best meet the query conditions over incomplete database not trivial task. Several techniques have been proposed to process database. Some these retrieve based on existing values rather than estimating missing values. Such are undesirable cases dimensions with might be important user’s query. Besides, output satisfy user preferences. In this paper we propose an approach estimates skylines guide users selecting most appropriate from several candidate skylines. utilizes concept mining attribute correlations generate Approximate Functional Dependencies (AFDs) captured relationships between dimensions. identifying strength probability estimate Then, estimated ranked. By doing so, ensure retrieved order their precision.
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