| Summary: | 碩士 === 國立東華大學 === 資訊工程學系 === 100 === Because of the development of modern technology, a huge amount of data is produced and changing over time. In a data stream environment, the information is keeping updating; since previous methods which are used in static dataset can neither adopt in stream environment, nor satisfied the needs of users. Therefore, how to find out the data which people are concerned in stream environment becomes an important issue. Top-k dominating query combines the advantages of top-k query and skyline query, not only allow users to control the number of results------ return k objects which have highest dominating score in dataset; but also provide an intuitive ranking function based on dominating score, so users don’t need to design ranking functions themselves.
In this thesis, we discuss the problem of finding top-k dominating query in a data stream environment and propose an efficient approximation algorithm, named EAA, for finding the satisfied data with high accuracy. The experimental results show that EAA can answer the result of top-k dominating query faster than previous approaches, and achieve a high accuracy.
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