PREFER: a system for the efficient execution of multi-parametric ranked queries

By Vagelis Hristidis, Nick Koudas, Yannis Papakonstantinou. ACM SIGMOD Conference, 2001

320 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b47283c7d69d0116e656beb6ddcc64e97dbaef57

How researchers see this paper

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

In Signal Processing

Citations in the corpus

A survey of top-k query processing techniques in relational database systems (2008, methodology): “Using materialized views for top-k processing has been studied in the PREFER system [Hristidis et al. 2001; Hristidis and Papakonstantinou 2004], which answers preference queries using materialized views.”
Skyline with presorting (2003, background): “Skyline has prompted much interest recently, as people see its potential as a basis for—or at least a major component of—efforts to provide preference queries over relational database systems [1, 3, 6, 7, 8].”
Stabbing the sky: efficient skyline computation over sliding windows (2005, background): “The techniques can be found in the literature [12, 13, 22, 24].”
Progressive skyline computation in database systems (2005, methodology): “queries include Prefer [ HKP01 ] and Onion [CBC+00] that are based on pre-materialization and convex”
Efficient IR-Style Keyword Search over Relational Databases (2003, methodology): “The design of the pipelined algorithms that we propose in this paper faces challenges that are related to other top-k work (e.g., [14, 6, 10, 4]).”
Evaluating top-k queries over Web-accessible databases (2002, methodology): “Additional related work includes the PREFER system [11], which uses pre-materialized views to efficiently answer ranked preference queries over commercial DBMSs.”
Preference SQL - Design, Implementation, Experiences (2002, background): “Other recent work on preferences can be found in [AgW00, HKP01, Cho02].”
Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease (2010, background): “…exhibiting an outstanding combination of both criteria using the skyline operator which has been successfully applied in many multi-criteria decision making applications, e.g. in personalized information systems (Hristidis et al., 2001) or for the selection of web services (Skoutas et al., 2008).”
RankSQL: query algebra and optimization for relational top-k queries (2005, background): “In RDBMS, there have been several proposals to support answering top-k queries at application level or outside the core of query engines [6, 5, 29, 14, 15, 20, 31], or for supporting special types of ranking queries [25, 21].”
Efficient Computation of the Skyline Cube (2005, background): “This is mainly due to the importance of skyline results in many applications, such as multi-criteria decision making [6], data mining and visualization [13], and user-preference queries [12].”
Preference formulas in relational queries (2003, methodology): “Nevertheless, only recently this area has attracted broader interest in the database research community [Agrawal and Wimmers 2000; Börzsönyi et al. 2001; Govindarajan et al. 2001; Hristidis et al. 2001; Chomicki 2002; Kießling 2002; Kießling and Hafenrichter 2002; Kießling and Köstler 2002].”