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Displaying 1-3 out of 3 total
Topic diversity in tag recommendation
Found in: Proceedings of the 7th ACM conference on Recommender systems (RecSys '13)
By Fabiano Belém, Jussara Almeida, Marcos Gonçalves, Rodrygo Santos
Issue Date:October 2013
pp. 141-148
Tag recommendation approaches have historically focused on maximizing the relevance of the recommended tags for a given object, such as a movie or a song. Nevertheless, different users may be interested in the same object for different reasons---for instan...
A relevance feedback approach for the author name disambiguation problem
Found in: Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries (JCDL '13)
By Anderson A. Ferreira, Ariadne M.B.R. Carvalho, Edward A. Fox, Marcos A. Gonçalves, Ricardo da S. Torres, Thiago A. Godoi, Weiguo Fan
Issue Date:July 2013
pp. 209-218
This paper presents a new name disambiguation method that exploits user feedback on ambiguous references across iterations. An unsupervised step is used to define pure training samples, and a hybrid supervised step is employed to learn a classification mod...
Automatic query expansion based on tag recommendation
Found in: Proceedings of the 21st ACM international conference on Information and knowledge management (CIKM '12)
By Fabiano Belém, Guilherme Gomes, Jussara Almeida, Marcos Gonçalves, Nivio Ziviani, Vitor Oliveira, Wladmir Brandão
Issue Date:October 2012
pp. 1985-1989
We here propose a new method for expanding entity related queries that automatically filters, weights and ranks candidate expasion terms extracted from Wikipedia articles related to the original query. Our method is based on state-of-the-art tag recommenda...