Ranking academic institutions on potential paper acceptance in upcoming conferences

October 10, 2016 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Jobin Wilson, Ram Mohan, Muhammad Arif, Santanu Chaudhury, Brejesh Lall arXiv ID 1610.02828 Category cs.AI: Artificial Intelligence Cross-listed cs.DL, cs.LG Citations 5 Venue arXiv.org Last Checked 4 months ago
Abstract
The crux of the problem in KDD Cup 2016 involves developing data mining techniques to rank research institutions based on publications. Rank importance of research institutions are derived from predictions on the number of full research papers that would potentially get accepted in upcoming top-tier conferences, utilizing public information on the web. This paper describes our solution to KDD Cup 2016. We used a two step approach in which we first identify full research papers corresponding to each conference of interest and then train two variants of exponential smoothing models to make predictions. Our solution achieves an overall score of 0.7508, while the winning submission scored 0.7656 in the overall results.
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