Paper Title:
Query Optimization Based on Data Provenance
  Abstract

Data Provenance is a key of evaluating authority and uncertainty in data query. Query process technology based on data provenance overcomes the shortcomings of traditional data integration on query quality and efficiency. This paper constructs a data model of heterogeneous data sources provenance, i.e. Semiring Provenance, based on tracing provenance of data origination and evolution. It’s proved to be effective in creating mapping between heterogeneous schemas and optimizing query quality and authority evaluation. Experiments using real data set show that our approach provides an effective and scalable solution for query optimization technology.

  Info
Periodical
Edited by
Wenya Tian and Linli Xu
Pages
586-590
DOI
10.4028/www.scientific.net/AMR.186.586
Citation
L. Huang, H. B. Cheng, "Query Optimization Based on Data Provenance", Advanced Materials Research, Vol. 186, pp. 586-590, 2011
Online since
January 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Jun Qiang Liu, Xiao Ling Guan
Abstract:Semantic data management is a key issue in PDM (product data management) system. Traditional PDM system is not suitable for complex semantic...
1024
Authors: Shu Dong Zhang, Zhen Xing Sun, Ning Luo
Abstract:We design and implement a kind of dynamic report model in Silverlight application which based on TelerikReporting component and the...
872
Authors: Shu Fang Zhao, Li Chao Chen
Chapter 3: Sensor, Test and Signal Processing
Abstract:Data mining is the process of abstracting unaware, potential and useful information and knowledge from plentiful, incomplete, noisy, fuzzy...
731
Authors: Rui Lian Hou, Ai Mei Dong, Xiu Fang Li
Chapter 3: Material Science, Manufacturing Engineering and Production System
Abstract:This paper provides the schemata and arithmetic of the city ambient air quality monitoring data warehouse. And describes the Modeling Theory...
616
Authors: Cui Fang Zheng, Long Jiang, Li Qing Jiang, Zhi Jie Wu
Chapter 5: Information Processing and Computational Science
Abstract:Data mining techniques give us a feasible method to deal with great amount of data, which is generated during the software developing. Many...
738