Feature Engineering for Supervised Link Prediction on Dynamic Social Networks
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Summary
A two-step solution strategy to the link prediction problem in dynamic networks in this work involves a novel yet simple feature construction approach using a combination of domain and topological attributes of the graph.
- Type
- preprint
- Published
- 2014-10-07
- Cited by
- 8
- References
- 18
- Access
- Open access
- OpenAlex
- https://openalex.org/W45251512
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:11311905
Keywords
Computer science, Machine learning, Artificial intelligence, Feature selection, Process (computing)
References
- Link Prediction in Complex Networks: A Survey
- New perspectives and methods in link prediction
- Link mining: a survey
- A PCA-based similarity measure for multivariate time series
- Mining knowledge-sharing sites for viral marketing
- Co-author Relationship Prediction in Heterogeneous Bibliographic Networks
- LIBLINEAR: A Library for Large Linear Classification
- Exploring Network Structure, Dynamics, and Function using NetworkX
- The Time-Series Link Prediction Problem with Applications in Communication Surveillance
- LIBSVM: A library for support vector machines
- Learning spectral graph transformations for link prediction
- The link prediction problem for social networks
- Link prediction using supervised learning
- Link Prediction in Heterogeneous Networks : Influence and Time Matters
- Natural Language Processing with Python
- SciPy: Open Source Scientific Tools for Python
- Link Prediction via Matrix Factorization
Cited by
- Link Prediction in Microblog Network Using Supervised Learning with Multiple Features
- Preserving Community Feature Extraction And Mrmr Feature Selection For Link Classification In Complex Networks
- Temporal Link Prediction: A Survey
- Recommendations in Social Network using Link Prediction Technique
- An approach for predicting missing links in social network using node attribute and path information
- Feature Engineering (FE) Tools and Techniques for Better Classification Performance
- A matrix factorization model with local and global consistency for flow prediction in bike-sharing systems
- BT-LPD: B+[12pt]minimal amsmath wasysym amsfonts amssymb amsbsy mathrsfs upgreek -69pt document^+document Tree-Inspired Community-Based Link Predic
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