The link prediction problem for social networks
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Summary
Experiments on large co-authorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
- Type
- article
- Published
- 2003-11-03
- Cited by
- 2,960
- References
- 43
- Access
- Open access
- OpenAlex
- https://openalex.org/W2420733993
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:207906022
Keywords
Link (geometry), Computer science, Link analysis, Computer network, Machine learning
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- A bibliometric analysis of collaboration in the field of Information Retrieval
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- Increasing the Predictive Power of Affiliation Networks
- Implicit Structure and the Dynamics of Blogspace
- Fast Incremental and Personalized PageRank
- Impact of multimedia in Sina Weibo
- Identifying Graphs from Noisy Observational Data
- A framework for the static and dynamic analysis of interaction graphs
- Name Reference Resolution in Organizational Email Archives
- Semantic Social Networks Constructed by Topical Aspects of Conversations: An Explorative Study
- On the predictability of recurring links in networks of face-to-face proximity
- Detecting Communities in Social Networks Using Max-Min Modularity
- Collective entity resolution in relational data
- Mining communities in networks: a solution for consistency and its evaluation
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