GAIA: graph classification using evolutionary computation

By Ning Jin, Calvin Young, Wei Wang. 2010

83 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems

How researchers see this paper

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

In Artificial Intelligence

1. Michalis Vazirgiannis
2. François Rousseau
3. Emmanouil Kiagias
4. Konstantinos Skianis
5. Fragkiskos D. Malliaros
6. Jamie Callan
7. Zhuyun Dai

In Computer Vision and Pattern Recognition

1. Michalis Vazirgiannis
2. Emmanouil Kiagias
3. François Rousseau

In Information Systems

1. Michalis Vazirgiannis
2. Emmanouil Kiagias
3. François Rousseau
4. Konstantinos Skianis
5. Fragkiskos D. Malliaros

Citations in the corpus

• Text Categorization as a Graph Classification Problem (2015, background): “However, when experimenting, gBoost did not converge on our larger datasets while GAIA and CORK consider subgraphs of node size at least 2, which exclude unigrams, resulting in poorer performances.”