Impact Factor:6.549
 Scopus Suggested Journal: Tracking ID for this title suggestion is: 55EC484EE39417F0

International Journal
of Computer Engineering in Research Trends (IJCERT)

Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

Welcome to IJCERT

International Journal of Computer Engineering in Research Trends. Scholarly, Peer-Reviewed, Platinum Open Access and Multidisciplinary

ISSN(Online):2349-7084                 Submit Paper    Check Paper Status    Conference Proposal

Back to Current Issues

Query Aware Determinization of Uncertain Objects

P.Jhancy, K.Lakshmi , Dr.S.Prem Kumar, ,
Pursuing M.Tech, CSE Branch, Dept of CSE
Assistant 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 – 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 :,

Keywords : uncertain data, query workload, data quality, branch and bound algorithm.

[1] D. V. Kalashnikov, S. Mehrotra, J. Xu, and N. Venkatasubramanian, “A semantics-based approach for speech annotation of images,” TKDE’11. 
[2] J. Li and J. Wang, “Automatic linguistic indexing of pictures by a statistical modeling approach,” PAMI’03. 
[3] C. Wangand, F. Jing, L. Zhang, and H. Zhang, “Image annotation refinement using random walk with restarts,” ACM Multimedia’06. 
[4] B. Minescu, G. Damnati, F. Bechet, and R. de Mori, “Conditional use of word lattices, confusion networks and 1-best string hypotheses in a sequential interpretation strategy,” ICASSP’07.
 [5] R. Nuray-Turan, D. V. Kalashnikov, S. Mehrotra, and Y. Yu, “Attribute and object selection queries on objects with probabilistic attributes,” ACM TODS’11. 
[6] J. Li and A. Deshpande, “Consensus answers for queries over proba-bilistic databases,” PODS’09. 
[7] M. B. Ebarhimi and A. A. Ghorbani, “A novel approach for frequent phrase mining in web search engine query streams,” CNSR ’07.
 [8] S. Bhatia, D. Majumdar, and P. Mitra, “Query suggestions in the absence of query logs,” SIGIR ’11. 
[9] C. Manning and H. Schutze, Foundations of Statistical Natural Lan-guage Processing. MIT Press, 1999. 
[10] D. V. Kalashnikov and S. Mehrotra, “Domainindependent data cleaning via analysis of entityrelationship graph,” ACM TODS’06. 
[11] K. Schnaitter, S. Abiteboul, T. Milo, and N. Polyzotis, “On-line index selection for shifting workloads,” SMDB’07.
 [12] P. Unterbrunner, G. Giannikis, G. Alonso, D. Fauser, and D. Kossmann, “Predictable performance for unpredictable workloads,” VLDB’09. 
[13] R. Cheng, J. Chen, and X. Xie, “Cleaning uncertain data with quality guarantees,” PVLDB’08. V. Jojic, S. Gould, and D. Koller, “Accelerated dual decomposition for map inference,” ICML ’1


Download :

Refbacks : Currently there are no Refbacks

Support Us

We have kept IJCERT is a free peer-reviewed scientific journal to endorse conservation. We have not put up a paywall to readers, and we do not charge for publishing. But running a monthly journal costs is a lot. While we do have some associates, we still need support to keep the journal flourishing. If our readers help fund it, our future will be more secure.

Quick Links


Science Central

Score: 13.30

Submit your paper to