Title :
Semantic Model Based Heterogeneous Databases Integration Platform
Author :
Zhao, Han ; Zhang, Shusheng ; Zhou, Jingtao ; Wang, Mingwei
Author_Institution :
Northwestern Polytech. Univ., Xian
Abstract :
Enterprise need integrate all relevant heterogeneous databases in semantic level to react to requirements of their customers, collaborate with partners, identify and exploit new business opportunities quickly and effectively. In this context, a semantic model based Integration platform is developed to cover the whole integration process. The platform includes three modules corresponding to different integration stages: 1) metadata abstraction module is used to get available metadata for attribute correspondence identification. 2) semantic matching module is applied to analyze the metadata and find attributes in different databases that represent the same real-world concept. 3) user checking module adopt semantic model construction principle to describe the matching results as a draft semantic model and provide user editing tool to check and improve the draft model. This document describes the architecture of our platform, walks through its most important two features: machine learning technology based attributes matching and semantic model construction principle.
Keywords :
distributed databases; formal verification; learning (artificial intelligence); meta data; attribute correspondence identification; heterogeneous databases integration; machine learning; metadata abstraction; semantic matching; semantic model construction principle; user checking; user editing tool; Collaboration; Context modeling; Databases; Educational technology; Laboratories; Machine learning; Modular construction; Neural networks; Object oriented modeling; Virtual manufacturing;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.656