Affiliations Pursuing M.Tech, CSE Branch, Dept of CSEAssistant Professor, Department of Computer Science and Engineering</br>Professor & HOD, Department of computer science and engineering, G.Pullaiah College of Engineering and Technology, Kurnool, Andhra Pradesh, India.
The main aim of this paper is to think about the trouble of determining probabilistic data to allow such data
to be stored in legacy systems that agree only deterministic input. Probabilistic data may be produced by mechanized
data analysis methods such as entity resolution, information extraction, and speech processing etc. The target is to make
a deterministic depiction of probabilistic data that optimizes the excellence of the end-application built on deterministic
data. We discover such a determinization problem in the background of two dissimilar data processing jobs â€“ selection
and triggers queries. Here approaches such as thresholding or top-1 selection usually used for determinization lead to
suboptimal presentation for such applications. As an alternative, we expand a query-aware strategy and demonstrate its
rewards over existing solutions through a complete empirical evaluation over real and synthetic datasets.
P.Jhancy,K.Lakshmi,Dr.S.Prem Kumar."Query Aware Determinization of Uncertain Objects". International Journal of Computer Engineering In Research Trends (IJCERT) ,ISSN:2349-7084 ,Vol.2, Issue 12,pp.904-907, December - 2015, URL :https://ijcert.org/ems/ijcert_papers/V2I1217.pdf,
Keywords : uncertain data, query workload, data quality, branch and bound algorithm.
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