TALE: A Tool for Approximate Large Graph Matching

By Yuanyuan Tian, Jignesh M. Patel. IEEE International Conference on Data Engineering, 2008

329 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/45e68c8a2fa034cb0e4a94bf51d2189ca598e5f8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Wook-Shin Han
2. Romans Kasperovics
3. Jeong-Hoon Lee
4. Jiong Yang
5. Shijie Zhang
6. Shirong Li
7. Jinsoo Lee

In Computer Vision and Pattern Recognition

1. Wook-Shin Han
2. Jeong-Hoon Lee
3. Jinsoo Lee
4. Romans Kasperovics
5. Jiong Yang
6. Shijie Zhang
7. Shirong Li

In Hardware and Architecture

1. Wook-Shin Han
2. Romans Kasperovics
3. Jeong-Hoon Lee
4. Jiong Yang
5. Shijie Zhang
6. Shirong Li
7. Jinsoo Lee

Citations in the corpus

• An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases (2012, methodology): “Rep-resentative algorithms in this area include TALE [13], SIGMA [9], and Ness [6].”
• Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases (2013, background): “Research efforts on approximate subgraph search algorithms [15, 9, 7] are also active.”
• The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees (2013, methodology): “The GADDI algorithm [18] on the other hand deals with larger graphs and uses an indexing based on a neighborhood structure, similar to the TALE algorithm [19].”
• GADDI: distance index based subgraph matching in biological networks (2009, methodology): “In TALE [40], an approximate matching method was proposed for large query graphs based on neighborhood units.”