A Graph Pattern Matching Method Supporting Fuzzy Constraint Relations

Abstract

The present invention provides a graph pattern matching method for supporting a fuzzy constraint relation, which relates to the technical field of graph information query and is used for solving the problem, in the prior art, of failing to support matching of a fuzzy constraint relation on the basis of meeting all accurate constraints. The method comprises: by means of an input layer, acquiring a query graph Q input by a user and a stored target data graph G, wherein the query graph contains the accurate constraint relation and the fuzzy constraint relation; by means of an accurate matching layer, performing accurate map matching for the accurate constraint relation in the query graph input by the user in the target data graph, and constructing a guide graph with a merging node in the target data graph; and by means of a fuzzy search layer, finding out and outputting K matching graphs that have the best fuzzy constraint matching quality on the basis of meeting all the accurate constraints in the guide graph. The graph pattern matching method for supporting the fuzzy constraint relation is applicable for performing hybrid query supporting the fuzzy constraint relation and the accurate constraint relation in massive target data graphs.

Description

technical field [0001] The invention relates to the technical field of graph information query, in particular to a graph pattern matching method supporting fuzzy constraint relationships. Background technique [0002] In recent years, with the development of Internet technology, more and more social networks have appeared one after another, such as large-scale online social networking sites represented by Facebook, Twitter, Sina Weibo, etc. relationship network, etc. At present, these networks show the following characteristics: 1. The scale of the network continues to expand. How to regard users as fixed points and the relationship between them as edges, then the constructed network will gradually become a massive information network. 2. There are many types of user attributes and relationships, and different social networks usually have different user attributes and relationship types. How to extract valuable information from this massive network is a hot spot of many re...

AI Technical Summary

Problems solved by technology

[0005] However, the existing graph pattern matching methods cannot meet the following practical analysis requirements: With the increase of network scale and the heterogeneity of network information, it is difficult for users to construct accurate query graphs required by applications

Usually only a part of the connection relationship and fuzzy constraint relationship of precise constraints can be given (only the connectivity of nodes is required), for example, looking for two groups with special attributes in a social network to complete an entrepreneurial project or marketing strategy, the members of the group The connection constraint relationship and attributes are known through the application background, but there is no precise constraint on how the teams are connected, but they are required to be connected in the least costly way

If you rely on users to manually process fuzzy constraints, enumerate all possible connection relationships, and then use existing methods to query, it will require a huge amount of work, and the time and space overhead will be huge

In addition, if the existing independent point query graph method is directly used, it cannot be guaranteed to satisfy the given other precise constraints

Therefore, existing technical methods cannot support the matching of fuzzy constraint relationships on the basis of satisfying all precise constraints.

Images