The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Supervised random walks: predicting and recommending links in social networks
Abstract
Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interactions among existing members are likely to occur in the near future or which existing interactions are we missing. Although this problem has been extensively studied, the challenge of how to effectively combine the information from the network structure with rich node and edge attribute data remains largely open.
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Cites
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Self-citationHierarchical structure and the prediction of missing links in networks
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Group formation in large social networks: membership, growth, and evolution
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Cited by
node2vec: Scalable Feature Learning for Networks
Grover, A., & Leskovec, J. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining · doi:10.1145/2939672.2939754 · Cited by 10,926
Self-citationFeature Selection: A Data Perspective
Li, J., Cheng, K., Wang, S., Morstatter, F., Trevino, R. P., Tang, J., & Liu, H. (2018) · ACM Computing Surveys · doi:10.1145/3136625 · Cited by 2,442
Graph convolutional networks: a comprehensive review
Zhang, S., Tong, H., Xu, J., & Maciejewski, R. (2019) · Computational Social Networks · doi:10.1186/s40649-019-0069-y · Cited by 1,888
GNNExplainer: Generating Explanations for Graph Neural Networks
Ying, R., Bourgeois, D., You, J., Zitnik, M., & Leskovec, J. (2019) · arXiv · doi:10.48550/arxiv.1903.03894 · Cited by 850
Self-citationWTF: the who to follow service at Twitter
Gupta, P., Goel, A., Lin, J., Sharma, A., Wang, D., & Zadeh, R. (2013) · Proceedings of the 22nd international conference on World Wide Web · doi:10.1145/2488388.2488433 · Cited by 461
Metadata
- Authors
- Backstrom, L., & Leskovec, J.
- Venue
- Proceedings of the fourth ACM international conference on Web search and data mining
- Publisher
- ACM
- Published
- 2011-02-09
- Pages
- 635-644
- OpenAlex
- W2107569009
- Cited by
- 982
- References
- 29
- FWCI
- 74.87
- Type
- conference paper
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
