International Journal of Advanced Information and Communication Technology


Object Search Pattern Application using Queries

M. Niveditha, K. Sivachandran, Sasurie Academy of Engineering, Coimbatore, Tamilnadu, India.

DOI : 01.0401/ijaict.2016.11.02

International Journal of Advanced Information and Communication Technology

Received On : March 12, 2019

Revised On : April 10, 2019

Accepted On : May 13, 2019

Published On : June 05, 2019

Volume 06, Issue 06

Pages : 1078-1081

Abstract


This survey concern with the problem of determinizing probabilistic data which accept only deterministic input by accepting this type of input data to be stored in legacy systems. The automated data analysis/enrichment techniques Probabilistic data may be generated. These techniques are entity resolution, information extraction, and speech processing. The legacy application system may belong to the pre-existing web applications like Flicker, Picasa, etc. The big aim is to generate a deterministic representation of probabilistic data which optimizes the deterministic data quality on the end-application. Those type of determinization problem should be deployed in the context of two different data processing tasks—triggers and selection queries. Thresholding or top-1 selection techniques are traditionally used for determinization which lead to suboptimal performance for many applications. Instead this survey proposes a query-aware strategy and explains its advantages over existing solutions through a comprehensive empirical study over real and synthetic datasets.

Keywords


Determination, Uncertain Data, Data Quality, Query Workload, Branch and Bound Algorithm.

Cite this article


M. Niveditha, K. Sivachandran, “Object Search Pattern Application using Queries” INTERNATIONAL JOURNAL OF ADVANCED INFORMATION AND COMMUNICATION TECHNOLOGY, pp.1078-1081, June 05, 2019.

Copyright


© 2019 M. Niveditha, K. Sivachandran. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.