Abstract
Preference queries enable satisfying search results by delivering best matches, even when no tuple in a dataset fulfills all preferences perfectly. Several methods were developed for preference query processing, such as window-based, distributed, divide-and-conquer, and index-based algorithms. In particular, all index-based algorithms were designed to evaluate Pareto preferences, where the participating preferences are all equally important. In this paper we present index structures for base preferences. Our comprehensive experiments show how indexing data for preference database queries enable faster access of the data tuples and therefore lead to performance advantages when evaluating preferences.
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We used the Java Runtime object with the methods totalMemory() and freeMemory() to determine the total amount of used memory in the JVM.
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Endres, M., Weichmann, F. (2017). Index Structures for Preference Database Queries. In: Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T., Legind Larsen, H. (eds) Flexible Query Answering Systems. FQAS 2017. Lecture Notes in Computer Science(), vol 10333. Springer, Cham. https://doi.org/10.1007/978-3-319-59692-1_12
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DOI: https://doi.org/10.1007/978-3-319-59692-1_12
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