Identifying Relevant Matches with NOT Semantics over XML Documents

Keyword search over XML documents has been widely studied in recent years. It allows users to retrieve relevant data from XML documents without learning complicated query languages. SLCA (smallest lowest common ancestor)-based keyword search is a common mechanism to locate the desirable LCAs for the given query keywords, but the conventional SLCA-based keyword search is for AND-only semantics. In this paper, we extend the SLCA keyword search to a more general case, where the keyword query could be an arbitrary combination of AND, OR, and NOT operators. We further define the query result based on the monotonicity and consistency properties, and propose an efficient algorithm to figure out the SLCAs and the relevant matches. Since the keyword query becomes more complex, we also discuss the variations of the rnonotonicity and consistency properties in our framework. Finally, the experimental results show that the proposed algorithm runs efficiently and gives reasonable query results by measuring the processing time, scalability, precision, and recall.