Sampling Multiple Nodes in Large Networks-Reference-Cited by-同舟云学术

Sampling Multiple Nodes in Large Networks

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
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Author:

Ben-Eliezer Omri¹,Eden Talya²,Oren Joel³,Fotakis Dimitris⁴

Affiliation:

1. Harvard University & Massachusetts Institute of Technology, Cambridge, MA, USA

2. Boston University & Massachusetts Institute of Technology, Boston, MA, USA

3. Bosch Center for Artificial Intelligence, Haifa, Israel

4. National Technical University of Athens, Athens, Greece

Funder

National Science Foundation

Eric and Wendy Schmidt Fund for Strategic Innovation

National Technical University of Athens

Ben-Gurion University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498383

Reference60 articles.

1. K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases

2. Efficient algorithms for large-scale local triangle counting

3. Omri Ben-Eliezer , Talya Eden , Joel Oren , and Dimitris Fotakis . Sampling multiple nodes in large networks: Beyond random walks. CoRR, abs/2110.13324 , 2021 . Omri Ben-Eliezer, Talya Eden, Joel Oren, and Dimitris Fotakis. Sampling multiple nodes in large networks: Beyond random walks. CoRR, abs/2110.13324, 2021.

4. Link Prediction in Networks with Core-Fringe Data

5. How to Count Triangles, without Seeing the Whole Graph

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