Identifying skylines in dynamic incomplete database

Nowadays in database systems finding the best results that meet the preferences of users is the most important issue. Skyline queries will present the data items that are not being dominated by the other items in a database. Most of the operations assume the database is complete which means there are no missing values in the database dimensions. In reality, databases are not complete especially for multidimensional database. Missing values have a negative effect on finding skyline points. It changes the native of dominance relation, leads to cyclic dominance and unsatisfying the transitivity property of skylines. This problem becomes more severe in dynamic database in which new items are inserted or items are deleted or updated from the database. Besides, most of the works that handled the incomplete issue assumed that items are static. In this paper we propose the new approach which finds the most relevant data items that meet user’s preferences for dynamic incomplete databases

[1]  Wolf-Tilo Balke,et al.  Efficient Distributed Skylining for Web Information Systems , 2004, EDBT.

[2]  Hamidah Ibrahim,et al.  Finding skyline points over dynamic incompletedatabase , 2014 .

[3]  Hong Zou,et al.  Notice of RetractionFinding k-dominant skyline in dynamic data set , 2011, 2011 Seventh International Conference on Natural Computation.

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

[5]  Yufei Tao,et al.  Maintaining sliding window skylines on data streams , 2006, IEEE Transactions on Knowledge and Data Engineering.

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

[7]  Jian Pei,et al.  Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces , 2005, VLDB.

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

[9]  Bernhard Seeger,et al.  Progressive skyline computation in database systems , 2005, TODS.

[10]  Kian-Lee Tan,et al.  Stratified computation of skylines with partially-ordered domains , 2005, SIGMOD '05.

[11]  Hongjun Lu,et al.  Stabbing the sky: efficient skyline computation over sliding windows , 2005, 21st International Conference on Data Engineering (ICDE'05).

[12]  Hamidah Ibrahim,et al.  ESTIMATING MISSING VALUES OF SKYLINES IN INCOMPLETE DATABASE , 2013, DEIS 2013.

[13]  Beng Chin Ooi,et al.  Skyline Queries Against Mobile Lightweight Devices in MANETs , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[14]  Mohamed F. Mokbel,et al.  Skyline Query Processing for Incomplete Data , 2008, 2008 IEEE 24th International Conference on Data Engineering.

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

[16]  Jiawei Han,et al.  Mining Thick Skylines over Large Databases , 2004, PKDD.

[17]  P. Sreenivasa Kumar,et al.  Finding Skylines for Incomplete Data , 2013, ADC.

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

[19]  Qing Liu,et al.  Efficient Computation of the Skyline Cube , 2005, VLDB.

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