Query relaxation method for semantic association search on graph data

Abstract

A query relaxation method for semantic association search on graph data comprises the following steps: giving an entity association graph and diameter constraint, inputting a group of query entities, respectively calculating priorities of the query entities, then adding tuples < entities, initial entities and priorities > into a priority queue, and as long as the priority queue is not empty, taking out a tuple at the head of the queue; verifying the query entity, calculating the maximum successful sub-query set meeting the distance condition, and updating the optimal solution; and if the priority of the current entity cannot obtain a better solution, terminating and finishing the query. According to the method, the problem that the entity association search result is empty under the condition that the diameter is given on the graph data is solved, the query entity is relaxed, and it is guaranteed that association can be found through result sub-query.

Description

technical field [0001] The invention belongs to the technical field of computers, relates to graph search technology, and is a query relaxation method for semantic association search on graph data. Background technique [0002] Graph data has good expressive power, such as RDF data, which can intuitively show entities, that is, the complex relationship between points on the graph, and is applied in more and more fields. In particular, graph data is well suited for answering relational queries. That is to say, given several query entities on the graph, the query result is a connected subgraph that can contain these query entities, and the entities and their relationships represented by this subgraph are called semantic associations. [0003] There are many search techniques on the graph, the more basic ones are depth-first search, breadth-first search, and some variants of these two searches. These two methods are often inseparable when dealing with problems related to grap...

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Problems solved by technology

[0007] (3) It is the smallest, that is, none of its subsets can satisfy the above two conditions (1) (2)

A compact association can often show a closer and more meaningful relationship between entities, which also meets the needs of users, but this will cause a problem. After limiting the size of the semantic association, it may not be possible to find a subgraph that connects all query entities , so the results given by these methods may be empty, which causes a bad experience for the user

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