Giambattista Amati, Antonio Cruciani, Daniele Pasquini, Paola Vocca, Simone Angelini. propagate: A Seed Propagation Framework to Compute Distance-Based Metrics on Very Large Graphs. In Danai Koutra, Claudia Plant, Manuel Gomez-Rodriguez, Elena Baralis, Francesco Bonchi, editors, Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III. Volume 14171 of Lecture Notes in Computer Science, pages 671-688, Springer, 2023. [doi]
@inproceedings{AmatiCPVA23,
title = {propagate: A Seed Propagation Framework to Compute Distance-Based Metrics on Very Large Graphs},
author = {Giambattista Amati and Antonio Cruciani and Daniele Pasquini and Paola Vocca and Simone Angelini},
year = {2023},
doi = {10.1007/978-3-031-43418-1_40},
url = {https://doi.org/10.1007/978-3-031-43418-1_40},
researchr = {https://researchr.org/publication/AmatiCPVA23},
cites = {0},
citedby = {0},
pages = {671-688},
booktitle = {Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings, Part III},
editor = {Danai Koutra and Claudia Plant and Manuel Gomez-Rodriguez and Elena Baralis and Francesco Bonchi},
volume = {14171},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-031-43418-1},
}