Publication Type:

Conference Paper

Source:

Advances in Computational Intelligence - Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 509), Volume 509, p.pp.221-229 (2017)

URL:

https://link.springer.com/chapter/10.1007/978-981-10-2525-9_22

Keywords:

Attribute level, Distributed database, Ranking, Top-k query, Tuple level, uncertainty

Abstract:

In distributed database system, the data are located at different locations. As the data are at multiple locations, it may not be accurate. It may contain uncertain values or even some data may be missing. Due to impreciseness and uncertainty in the data, occurrence of error becomes high. This makes the processing of the data difficult. There are many ways to handle uncertain databases. To obtain required data, ranking technique is used. One such technique is the top-k query method where the data are retrieved according to user input. This paper proposes an algorithm that ranks and retrieves the data in minimum time at tuple level. In addition, the number of records traversed during this ranking and retrieval process is minimized. The time taken for retrieval of the records is also analyzed.

Cite this Research Publication

N. Lalithamani, “Ranking uncertain distributed databases at tuple level”, in Advances in Computational Intelligence - Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 509), 2017, vol. 509, pp. pp.221-229.

207
PROGRAMS
OFFERED
6
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
PARTNERS