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As data are increasingly modeled as graphs for expressing complexrelationships, the tree pattern query on graph-structured data becomes animportant type of queries in real-world applications. Most practical querylanguages, such as XQuery and SPARQL, support logical expressions usinglogical-AND/OR/NOT operators to define structural constraints of tree patterns.In this paper, (1) we propose generalized tree pattern queries (GTPQs) overgraph-structured data, which fully support propositional logic of structuralconstraints. (2) We make a thorough study of fundamental problems includingsatisfiability, containment and minimization, and analyze the computationalcomplexity and the decision procedures of these problems. (3) We propose acompact graph representation of intermediate results and a pruning approach toreduce the size of intermediate results and the number of join operations --two factors that often impair the efficiency of traditional algorithms forevaluating tree pattern queries. (4) We present an efficient algorithm forevaluating GTPQs using 3-hop as the underlying reachability index. (5)Experiments on both real-life and synthetic data sets demonstrate theeffectiveness and efficiency of our algorithm, from several times to orders ofmagnitude faster than state-of-the-art algorithms in terms of evaluation time,even for traditional tree pattern queries with only conjunctive operations.

Adding Logical Operators to Tree Pattern Queries on Graph-Structured Data