Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Artificial Intelligence - special issue on computational tradeoffs under bounded resources
A Data Set Oriented Approach for Clustering Algorithm Selection
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
The link-prediction problem for social networks
Journal of the American Society for Information Science and Technology
Scalable modeling of real graphs using Kronecker multiplication
Proceedings of the 24th international conference on Machine learning
A tutorial on spectral clustering
Statistics and Computing
LINKREC: a unified framework for link recommendation with user attributes and graph structure
Proceedings of the 19th international conference on World wide web
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
ISAC --Instance-Specific Algorithm Configuration
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A Unified Framework for Link Recommendation Using Random Walks
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Correcting for missing data in information cascades
Proceedings of the fourth ACM international conference on Web search and data mining
Improved call graph comparison using simulated annealing
Proceedings of the 2011 ACM Symposium on Applied Computing
Inferring Networks of Diffusion and Influence
ACM Transactions on Knowledge Discovery from Data (TKDD)
Community detection in incomplete information networks
Proceedings of the 21st international conference on World Wide Web
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An important area of social networks research is identifying missing information which is not explicitly represented in the network, or is not visible to all. Recently, the Missing Node Identification problem was introduced where missing members in the social network structure must be identified. However, previous works did not consider the possibility that information about specific users (nodes) within the network could be useful in solving this problem. In this paper, we present two algorithms: SAMI--A and SAMI--N. Both of these algorithms use the known nodes' specific information, such as demographic information and the nodes' historical behavior in the network. We found that both SAMI--A and SAMI--N perform significantly better than other missing node algorithms. However, as each of these algorithms and the parameters within these algorithms often perform better in specific problem instances, a mechanism is needed to select the best algorithm and the best variation within that algorithm. Towards this challenge, we also present OASCA, a novel online selection algorithm. We present results that detail the success of the algorithms presented within this paper.