Expressive top-k matching for conditional graph patterns

We propose conditional graph patterns (CGPs) that make conventional patterns more expressive, especially with positive and negative predicates. In emerging applications, CGPs allow to express complex search conditions and to find more sensible information than their traditional counterparts. We show that this expressivity does not come with a much higher price. Indeed, we propose a (parallel) matching algorithm that allows to match CGPs over any data graphs in quadratic time, as opposed to the prohibitive solutions based on subgraph isomorphism. In the second part of this article, we study the problem of top-k CGP matching algorithm. We propose the notion of relevance schema that allows users to define relevance criteria according to their preferences. We propose an early termination algorithm that finds the top-k relevant matches by requiring only 3%\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$3\%$$\end{document} of the time spent by the naive algorithm. To our knowledge, this is the first effort that investigates an expressive top-k graph pattern matching under simulation semantic. An extensive experimental study has been conducted to prove effectiveness and efficiency of our results.