Individual and Collective Graph Mining : Principles, Algorithms, and Applications /
Contenido: 1) Introducción. Parte I Minería gráfica individual: 2) Sumarización de gráficos estáticos; 3) Inferencia en un gráfico; Parte II Minería gráfica colectiva: 4) Sumarización de gráficos dinámicos; 5) Similitud de gráficos; 6) Alineación gráfica; 7) Conclusiones y problemas de investigación...
I tiakina i:
| Kaituhi matua: | |
|---|---|
| Ētahi atu kaituhi: | |
| Hōputu: | Pukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
[San Rafael, California] :
Morgan and Claypool,
2018, c2018
|
| Rangatū: | (Synthesis Lectures on Data Mining and Knowledge Discovery ;
14) |
| Ngā marau: | |
| Urunga tuihono: | Ver documento en línea |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
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