Abstract

In this paper, a novel type of interesting subgraph query is proposed: Minimal Unique Induced Subgraph (MUIS) query. Given a (large) graph G and a query vertex (position) q in the graph, can we find an induced subgraph containing q with the minimal number of vertices that is unique in G? MUIS query has many potential applications, such as subgraph retrieval, graph visualization, representative subgraph discovery and vertex property exploration. The formal definition of MUIS is given and the properties are discussed in this paper. The baseline and EQA (Efficient Query Answering) algorithms are proposed to solve the MUIS query problem under the filtering-validation framework. In the EQA algorithm, the Breadth First Search (BFS)-based candidate set generation strategy is proposed to ensure the minimality property of MUIS; the matched vertices-based pruning strategy is proposed to prune useless candidate sets and the unnecessary subgraph isomorphism; and the query position-based subgraph isomorphism is proposed to check efficiently the uniqueness of the subgraphs. Experiments are carried on real datasets and synthetic datasets to verify the effectiveness and efficiency of the proposed algorithm under novel measurements. The influencing factors of the process speed are discussed at last in the paper.

Highlights

  • Graphs have been used to model many complex data objects and their relationships in our real world, such as bioinformatics, chemistry, social networks, software, the World Wide Web, and so on [1,2,3,4,5,6]

  • Medical staff needs to query whether a given compound contains a particular substructure, and scientists want to query the number of specific substructures such as triangle subgraphs in the graph database

  • Minimal Unique Induced Subgraph (MUIS) query enriches and develops graph data query and management methods; For the novel type of subgraph query, the formal definition is given and the properties are discussed in this paper; The EQA (Efficient Query Answering) algorithm is proposed to solve the MUIS query problem under the filtering-validation framework

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Summary

Introduction

Graphs have been used to model many complex data objects and their relationships in our real world, such as bioinformatics, chemistry, social networks, software, the World Wide Web, and so on [1,2,3,4,5,6]. A novel type of interesting subgraph query is proposed. MUIS query provides a new graph data access and management method that has many potential applications, such as subgraph retrieval, graph visualization, representative subgraph discovery and vertex property exploration. MUIS query enriches and develops graph data query and management methods; For the novel type of subgraph query, the formal definition is given and the properties are discussed in this paper; The EQA (Efficient Query Answering) algorithm is proposed to solve the MUIS query problem under the filtering-validation framework. Search)-based candidate set generation strategy, matched vertices-based pruning strategy and query position-based subgraph isomorphism are proposed to improve the effectiveness and efficiency of MUIS query; Through comprehensive experiments on real datasets and synthetic datasets, EQA is demonstrated to outperform the state-of-the-art model to answer MUIS query.

Formal Definition and Properties
Subgraph Matching Query
Frequent Subgraph Mining
Correlation Subgraph Query
Network Motif Discovery
The Proposed Model
The General Framework
BFS-Based Candidate Set Generation Strategy
Matched Vertices-Based Pruning Strategy
Query Position-Based Subgraph Isomorphism
Baseline and EQA Algorithms
Results
Experimental Performance Measurement
Experiment on the YEAST Dataset
Experiment on the HPRD Dataset
Experiment on the Synthetic Datasets
Conclusions
Full Text
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