C4.5: programs for machine learning
C4.5: programs for machine learning
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
ACM SIGKDD Explorations Newsletter
A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Introduction to Information Retrieval
Introduction to Information Retrieval
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Finding potential research collaborators in four degrees of separation
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
CollabSeer: a search engine for collaboration discovery
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Time aware index for link prediction in social networks
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
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The scientific breakthroughs resulting from the collaborations between researchers often outperform the expectations. But finding the partners who will bring this synergic effect can take time and sometime gets nowhere considering the huge amounts of experts in various disciplines. We propose to build a link predictor in a network where nodes represent researchers and links - coauthorships. In this method we use the structure of the constructed graph, and propose to add a semantic and event based approach to improve the accuracy of the predictor. In this case, predictors might offer good suggestions for future collaborations. We will be able to compute the classification of a massive dataset in a reasonable time by under-sampling and balancing the data. This model could be extended in other fields where the research of partnership is important as in world of institutions, associations or companies. We believe that it could also help with finding communities of topics, since link predictors contain implicit information about the semantic relation between researchers.