期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
期号：MULTICON
页码：8
出版社：S&S Publications
摘要：Entity resolution is a fundamental problem in data integration dealing with the combination of data fromdifferent sources to a unified view of data. Entity Resolution is the task of identifying the same real-world object acrossdifferent entity profiles. It constitutes an inherently quadratic process, as it requires every entity profile to be comparedwith all others. The performance of entity resolution, as they process incoming identity records in three phases:recognize, resolve and relate. In the context of highly heterogeneous information spaces, an obstructive methoddepends on redundancy in order to ensure high effectiveness with lower efficiency. The coarse-grained blockprocessing techniques that discard entire blocks either priori or during the resolution process. These processes arepartially unsatisfactory and discard the entire block during resolution process. Entity resolution can reduce thecomplexity by proposing canonical references to particular entities and duplicating and linking entities. Duplication andorganize significantly reduced the complexity of the network from higher order graph to low order graph. In this paper,we introduce “Meta-Obstructive” as a generic procedure that intercede between the creation and processing with fewcomparisons with higher effectiveness. Entity Matching is an important and difficult step for integrating data. Thequality of obstructive collection is measured in terms of two criteria’s efficiency and effectiveness. To reduce the largespace for doing Entity Matching is time consuming. It compares most similar pairs of entities with more informationand encapsulate in entity relationships. It discards all redundant comparisons.
