Anisio Mendes Lacerda
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Learning to advertise
A Lacerda, M Cristo, MA Gonçalves, W Fan, N Ziviani, B Ribeiro-Neto
Proceedings of the 29th annual international ACM SIGIR conference on …, 2006
Pareto-efficient hybridization for multi-objective recommender systems
MT Ribeiro, A Lacerda, A Veloso, N Ziviani
Proceedings of the sixth ACM conference on Recommender systems, 19-26, 2012
Multiobjective pareto-efficient approaches for recommender systems
MT Ribeiro, N Ziviani, ESD Moura, I Hata, A Lacerda, A Veloso
ACM Transactions on Intelligent Systems and Technology (TIST) 5 (4), 1-20, 2014
A general framework to expand short text for topic modeling
P Bicalho, M Pita, G Pedrosa, A Lacerda, GL Pappa
Information Sciences 393, 66-81, 2017
Demand-driven tag recommendation
GV Menezes, JM Almeida, F Belém, MA Gonçalves, A Lacerda, ES Moura, ...
Joint European conference on machine learning and knowledge discovery in …, 2010
Multi-objective ranked bandits for recommender systems
A Lacerda
Neurocomputing 246, 12-24, 2017
A video summarization approach based on the emulation of bottom-up mechanisms of visual attention
H Jacob, FLC Pádua, A Lacerda, A Pereira
Journal of Intelligent Information Systems 49 (2), 193-211, 2017
Building user profiles to improve user experience in recommender systems
A Lacerda, N Ziviani
Proceedings of the sixth ACM international conference on Web search and data …, 2013
Minimal perfect hashing: A competitive method for indexing internal memory
FC Botelho, A Lacerda, GV Menezes, N Ziviani
Information Sciences 181 (13), 2608-2625, 2011
A robust indoor scene recognition method based on sparse representation
G Nascimento, C Laranjeira, V Braz, A Lacerda, ER Nascimento
Iberoamerican Congress on Pattern Recognition, 408-415, 2017
Topic modeling for short texts with co-occurrence frequency-based expansion
G Pedrosa, M Pita, P Bicalho, A Lacerda, GL Pappa
2016 5th Brazilian Conference on Intelligent Systems (BRACIS), 277-282, 2016
Guard: A genetic unified approach for recommendation
A Guimarães, TF Costa, A Lacerda, GL Pappa, N Ziviani
Journal of Information and Data Management 4 (3), 295-295, 2013
Improving daily deals recommendation using explore-then-exploit strategies
A Lacerda, RLT Santos, A Veloso, N Ziviani
Information Retrieval Journal 18 (2), 95-122, 2015
Multimodal data fusion framework based on autoencoders for top-N recommender systems
FLC Pádua, A Lacerda, AC Machado, DH Dalip
Applied Intelligence 49 (9), 3267-3282, 2019
Exploratory and interactive daily deals recommendation
A Lacerda, A Veloso, N Ziviani
Proceedings of the 7th ACM conference on recommender systems, 439-442, 2013
Weighted slope one predictors revisited
D Menezes, A Lacerda, L Silva, A Veloso, N Ziviani
Proceedings of the 22nd international conference on world wide web, 967-972, 2013
Detecting collaboration profiles in success-based music genre networks
GP Oliveira, MO Silva, DB Seufitelli, A Lacerda, MM Moro
Procs. Int’l Society for Music Information Retrieval Conference (ISMIR …, 2020
Contextual bandits for multi-objective recommender systems
A Lacerda
2015 Brazilian Conference on Intelligent Systems (BRACIS), 68-73, 2015
Using taxonomies for product recommendation
O Matos-Junior, N Ziviani, F Botelho, M Cristo, A Lacerda, AS da Silva
Journal of Information and Data Management 3 (2), 85-85, 2012
Evaluation of interest point matching methods for projective reconstruction of 3d scenes
DN Brito, CFG Nunes, FLC Padua, A Lacerda
IEEE Latin America Transactions 14 (3), 1393-1400, 2016
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