Faculty of Informatics and Statistics, Department of Information and Knowledge Engineering (DIKE)

Date and time: December 7 2017 (16:00 – 17:30).

Room: 469 NB Non–standard venue!


Using weighted centroids of word embeddings and top-k documents re-ranking for paper/project-reviewer recommendation


  • Martin Víta, NLP Centre, Faculty of Informatics, Masaryk University Brno

In this talk we present different approaches to content-based recommender systems that are based on centroids of word embeddings (word2vec in particular). This work is motivated by the paper/project-reviewer assignment problem and it will be demonstrated on the medical domain. We will demonstrate a system based on a known approach with TF-IDF centroid weighting + word-mover's distance re-ranking and also propose a novel method that uses weighting by closeness centrality in the word2vec word similarity graph.

Downloads: slides 1 

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