Preference evaluation techniques of preference queries in database

Preference queries are considered as a major necessity tool in today’s database management system (DBMS). Adopting preference queries in the database application systems enable users to determine more than one objective in the submitted query which result into more accurate results compared to the traditional queries. Preference queries prefer one data item (tuple) p over the other data item (tuple) q if and only if p is better than q in all dimensions (attributes) and not worse than q in at least one dimension (attribute). Several preference evaluation techniques for preference queries have been proposed which aimed at finding the “best” results that meet the user preferences. These include but not limited to top-k, skyline, ranked skylines, k-representative dominance, k-dominance,top-k dominating, and k-frequency. This paper attempts to survey and analyze the following preference evaluation techniques of query processing in database systems: top-k, skyline, top-k dominating, k-dominance, and k-frequency by highlighting the strengths and the weaknesses of each technique.

[1]  Raymond Chi-Wing Wong,et al.  Efficient skyline querying with variable user preferences on nominal attributes , 2008, Proc. VLDB Endow..

[2]  Wolf-Tilo Balke,et al.  Multi-objective Query Processing for Database Systems , 2004, VLDB.

[3]  Vagelis Hristidis,et al.  Algorithms and applications for answering ranked queries using ranked views , 2003, The VLDB Journal.

[4]  Donald Kossmann,et al.  Shooting Stars in the Sky: An Online Algorithm for Skyline Queries , 2002, VLDB.

[5]  Jarek Gryz,et al.  Maximal Vector Computation in Large Data Sets , 2005, VLDB.

[6]  Evaggelia Pitoura,et al.  BITPEER: continuous subspace skyline computation with distributed bitmap indexes , 2008, DaMaP '08.

[7]  Jan Chomicki,et al.  Skyline with presorting , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[8]  Ihab F. Ilyas,et al.  Supporting ranking queries on uncertain and incomplete data , 2010, The VLDB Journal.

[9]  Luis Gravano,et al.  Evaluating Top-k Selection Queries , 1999, VLDB.

[10]  Kyriakos Mouratidis,et al.  Continuous monitoring of top-k queries over sliding windows , 2006, SIGMOD Conference.

[11]  Christos Doulkeridis,et al.  On efficient top-k query processing in highly distributed environments , 2008, SIGMOD Conference.

[12]  Seung-won Hwang,et al.  Minimal probing: supporting expensive predicates for top-k queries , 2002, SIGMOD '02.

[13]  Wang Ruchuan,et al.  A Filter-Based Algorithm for Optimizing Top-k Queries in Wireless Sensor Networks , 2012 .

[14]  Anthony K. H. Tung,et al.  Skyline-join in distributed databases , 2008, 2008 IEEE 24th International Conference on Data Engineering Workshop.

[15]  Yuan Tian,et al.  Z-SKY: an efficient skyline query processing framework based on Z-order , 2010, The VLDB Journal.

[16]  Bernhard Seeger,et al.  An optimal and progressive algorithm for skyline queries , 2003, SIGMOD '03.

[17]  Beng Chin Ooi,et al.  Efficient Progressive Skyline Computation , 2001, VLDB.

[18]  Man Lung Yiu,et al.  Efficient Processing of Top-k Dominating Queries on Multi-Dimensional Data , 2007, VLDB.

[19]  Ilaria Bartolini,et al.  SaLSa: computing the skyline without scanning the whole sky , 2006, CIKM '06.

[20]  Donald Kossmann,et al.  The Skyline operator , 2001, Proceedings 17th International Conference on Data Engineering.

[21]  Mohamed F. Mokbel,et al.  Toward context and preference-aware location-based services , 2009, MobiDE.

[22]  Anthony K. H. Tung,et al.  On High Dimensional Skylines , 2006, EDBT.

[23]  Seung-won Hwang,et al.  Personalized top-k skyline queries in high-dimensional space , 2009, Inf. Syst..

[24]  Yannis Manolopoulos,et al.  Continuous Processing of Preference Queries in Data Streams , 2009, Conference on Current Trends in Theory and Practice of Informatics.

[25]  Yuan-Chi Chang,et al.  The onion technique: indexing for linear optimization queries , 2000, SIGMOD 2000.

[26]  Man Lung Yiu,et al.  Multi-dimensional top-k dominating queries , 2009, The VLDB Journal.