18520127. MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE simplified abstract (Huawei Technologies Co., Ltd.)
Contents
- 1 MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE
Organization Name
Inventor(s)
MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18520127 titled 'MULTI-SUBGRAPH MATCHING METHOD AND APPARATUS, AND DEVICE
Simplified Explanation
The multi-subgraph matching method and apparatus described in the abstract group query graphs based on hash values, match them with a data graph in parallel, and generate matching results between the query graphs and the data graph.
- Efficient grouping of query graphs based on hash values
- Parallel matching of grouped query graphs with a data graph
- Increased subgraph matching efficiency
Potential Applications
The technology can be applied in various fields such as:
- Bioinformatics
- Social network analysis
- Image recognition
Problems Solved
The technology addresses the following issues:
- Efficient grouping of query graphs
- Improved subgraph matching efficiency
Benefits
The benefits of this technology include:
- Faster subgraph matching process
- Enhanced performance in graph analysis tasks
Potential Commercial Applications
The technology can be utilized in commercial applications such as:
- Data mining software
- Pattern recognition systems
Possible Prior Art
One possible prior art is the use of hash values for grouping and matching in graph analysis tasks.
Unanswered Questions
How does the technology handle large-scale data graphs?
The article does not provide information on the scalability of the technology to handle large-scale data graphs.
What are the computational requirements of the multi-subgraph matching method?
The article does not mention the computational resources needed to implement the method.
Original Abstract Submitted
A multi-subgraph matching method and apparatus, and a device are provided. After receiving a plurality of query graphs, the multi-subgraph matching apparatus groups the plurality of query graphs based on a hash value of each query graph, to generate a plurality of groups of query graphs. A plurality of query graphs whose hash values fall within a same value range belong to a same group. Then, the multi-subgraph matching apparatus respectively matches the plurality of groups of query graphs with a data graph in parallel, to obtain matching results. The matching results are matching results between the plurality of query graphs and the data graph. According to the multi-subgraph matching method in this application, grouping efficiency can be increased, and subgraph matching efficiency can be effectively increased.
