Abstract
We consider a problem to select representative distinctive objects in a numerical database, which is an important problem in an early stage of knowledge discovery process. Skyline query and its variants are functions to find such representative objects. Skyline query selects representative objects that are not dominated by any other object in the dataset. Though skyline query is useful function, it cannot control the size of selected objects. In order to solve the problem, “top-k dominating query” and “K-skyband queries” have been introduced. However, conventional algorithms for computing those functions are not well suited for parallel distributed environment. In this paper, we consider a method for computing both queries in a parallel distributed framework called MapReduce, which is a popular framework to handle “big data”.
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Siddique, M.A., Tian, H., Morimoto, Y. (2014). Selecting Representative Objects from Large Database by Using K-Skyband and Top-k Dominating Queries in MapReduce Environment. In: Luo, X., Yu, J.X., Li, Z. (eds) Advanced Data Mining and Applications. ADMA 2014. Lecture Notes in Computer Science(), vol 8933. Springer, Cham. https://doi.org/10.1007/978-3-319-14717-8_44
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DOI: https://doi.org/10.1007/978-3-319-14717-8_44
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