Efficient Keyword Query Search over XML Data based on Context Based Diversification Technique
IJPRES ABSTRACT Empowering customers to get entry to databases by using easy keywords can relieve the users from the steep studying curve of mastering a structured query language and expertise complicated and possibly fast evolving data schemas.While key word query empowers general customers to search huge quantity of data, the paradox of keyword query makes ittough to correctly answer key word queries, especially for small and vague keyword queries. To deal with this tough hassle, inthis paper we suggest an approach that systematically diversifies XML key word search based on its distinctive contexts within the XML records.The proposed keyword search returns the set of smallest trees containing all keywords, where a tree is specified as "smallest" if it consists of no tree that also includes all keywords.Given a shortest and indistinct key word query and XML records to be searched, we first derive keyword seek candidates of the query through an easy feature selection model. and then, we design an powerful XML keyword search diversification version to find and calculate the first class of each candidate. After that, efficient algorithms are proposed to incrementally compute top k qualified query candidates as the assorted search intentions.At last, a complete evaluation on real and artificial information units demonstrates the effectiveness of our proposed diversification model and the efficiency of our algorithms.