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• W956380239 abstract "The prediction of new relationships in a social network is a complex and extremely useful task to enhance or maximize collaborations by indicating what the most promising partnerships are. In academic social networks, prediction of relationships is typically used to try to identify potential partners in the development of a project and/or co-authors for publishing papers. This paper presents a system that combines artificial intelligence techniques with the state-of-the-art metrics for link prediction. The resulting system was tested using real data from Computer Science researchers and achieved a precision above 99.5% in the co-authorship prediction." @default.
• W956380239 created "2016-06-24" @default.
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• W956380239 date "2015-05-26" @default.
• W956380239 modified "2023-09-26" @default.
• W956380239 title "A Link Prediction System in Social Networks" @default.
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• W956380239 doi "https://doi.org/10.5555/2814058.2814082" @default.
• W956380239 hasPublicationYear "2015" @default.
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