期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：7
DOI：10.15680/ijircce.2015. 0307015
出版社：S&S Publications
摘要：In various search mechanism keyword search is used and provides a simple but user friendly interface toextract or retrieve information from complicated data structure. As datasets are represented by trees and graph, but inreal life application the graph of that datasets are not certain. It is subjected to uncertainties due to incompleteness andambiguity of data. Because of its uncertainty, it is difficult task to retrieve keyword on uncertain graph, also it providesunwanted result. To overcome from this failure or drawback, this paper used new techniques. This technique provideseffective result for searching keyword on graph. Uncertain graph is used in PPI network, modeling Road network, RDFdata and social network etc. This technique takes less processing time and search the keyword with efficiency ascompared to previous research. Approximate mining algorithms i.e. K-Medoids Algorithm can be used to form subgraph from uncertain graph data based on scores at the level of keywords, data elements, element sets, and sub graphsthat connect these elements. To retrieve the efficient keyword from sub graph keyword matching algorithm i.e.selection sampling can be used for uncertain graph data. The objective of propose technique is to reduce the high costof processing keyword search queries on uncertain graph data and improve the performance of keyword search, withoutcompromising its result quality. Also o reduce processing time for keyword search in uncertain graph data.
