Skyline Query Processing for Incomplete Data

摘要: Recently, there has been much interest in processing skyline queries for various applications that include decision making, personalized services, and search pruning. Skyline aim to prune a space of large numbers multi dimensional data items small set interesting by eliminating are dominated others. Existing algorithms assume all dimensions available items. This paper goes beyond this restrictive assumption as we address the more practical case involving incomplete (i.e., missing values some their dimensions). In contrast complete where dominance relation is transitive, suffer from non-transitive which may lead cyclic behavior. We first propose two algorithms, namely, "Replacement" "Bucket" use traditional data. Then, "ISkyline" algorithm designed specifically The employs optimization techniques, virtual points shadow skylines tolerate relations. Experimental evidence shows significantly outperforms variations algorithms.