Enhanced Approach for Keyword Based Search on Uncertain Graph Data: A Review

Abstract

Author(s): Ashwini. V. Urade, Prof. Pravin Kulurkar

In many real applications, graph data is subjected to uncertainties due to incompleteness and imprecision of data. However, there is no work on keyword search over uncertain graph data even though the uncertain graphs have been widely used in real applications, such as modelling road networks, influential detection in social networks etc. Mining sub graphs is the ultimate goal of research on uncertain graph data management to retrieve the useful data from uncertain graph data. A keyword-element relationship summary that compactly represents relationships between keywords and the data elements mentioning them. Approximate mining algorithms can be used to form sub graph from uncertain graph data based on scores at the level of keywords, data elements, element sets, and sub graphs that connect these elements. To retrieve the efficient keyword from sub graph keyword matching algorithm can be used for uncertain graph data. The objective of propose technique is to reduce the high cost of processing keyword search queries on uncertain graph data and improve the performance of keyword search, without