Incremental Graph Pattern Matching Algorithm for Big Graph Data
نویسندگان
چکیده
منابع مشابه
A Incremental Graph Pattern Matching
Graph pattern matching is commonly used in a variety of emerging applications such as social network analysis. These applications highlight the need for studying the following two issues. First, graph pattern matching is traditionally defined in terms of subgraph isomorphism or graph simulation. These notions, however, often impose too strong a topological constraint on graphs to identify meani...
متن کاملIncremental Graph Pattern Matching: Data Structures and Initial Experiments
Despite the large variety of existing graph transformation tools, the implementation of their pattern matching engine typically follows the same principle. First a matching occurrence of the left-hand side of the graph transformation rule is searched by some graph pattern matching algorithm. Then potential negative application conditions are checked that might eliminate the previous occurrence....
متن کاملIncremental Pattern Matching in Graph-Based State Space Exploration
Graph pattern matching is among the most costly operations in any graph transformation system. Incremental pattern matching aims at reducing this cost by incrementally updating, as opposed to totally recalculating, the possible matches of rules in the graph grammar at each step of the transformation. In this paper an implementation of one such algorithm is discussed with respect to the GROOVE t...
متن کاملA Benchmark Evaluation of Incremental Pattern Matching in Graph Transformation
In graph transformation, the most cost-intensive phase of a transformation execution is pattern matching, where those subgraphs of a model graph are identified and matched which satisfy constraints prescribed by graph patterns. Incremental pattern matching aims to improve the efficiency of this critical step by storing the set of matches of a graph transformation rule and incrementally maintain...
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ژورنال
عنوان ژورنال: Scientific Programming
سال: 2018
ISSN: 1058-9244,1875-919X
DOI: 10.1155/2018/6749561