publications

2020

  1. Is Rank Aggregation Effective in Recommender Systems? An Experimental Analysis
    Oliveira, Samuel E. L., Diniz, Victor, Lacerda, Anı́sio, Merschmanm, Luiz, and Pappa, Gisele L.
    ACM Trans. Intell. Syst. Technol. 2020
  2. Explaining Symbolic Regression Predictions
    Filho, Renato Miranda, Lacerda, Anı́sio, and Pappa, Gisele L.
    In IEEE Congress on Evolutionary Computation, CEC 2020, Glasgow, United Kingdom, July 19-24, 2020 2020

2019

  1. Multimodal data fusion framework based on autoencoders for top-N recommender systems
    ao, Felipe L. A. Conceiç, Pádua, Flávio L. C., Lacerda, Anı́sio, Pereira, Adriano César Machado, and Dalip, Daniel Hasan
    Appl. Intell. 2019
  2. Multimodal approach for tension levels estimation in news videos
    Pereira, Moisés H. R., Pádua, Flávio L. C., Dalip, Daniel Hasan, Benevenuto, Fabrı́cio, Pereira, Adriano C. M., and Lacerda, Anı́sio M.
    Multim. Tools Appl. 2019
  3. On Modeling Context from Objects with a Long Short-Term Memory for Indoor Scene Recognition
    Laranjeira, Camila, Lacerda, Anı́sio, and Nascimento, Erickson R.
    In 32nd SIBGRAPI Conference on Graphics, Patterns and Images, SIBGRAPI 2019, Rio de Janeiro, Brazil, October 28-30, 2019 2019

2018

  1. A computational approach to support the creation of terminological neologisms in sign languages
    Souza, Celso L., Pádua, Flávio L. C., Lima, Vera L. S., Lacerda, Anı́sio, and Carneiro, Carlos A. G.
    Comput. Appl. Eng. Educ. 2018
  2. Exploiting Multiple Recommenders to Improve Group Recommendation
    Oliveira, Samuel E. L., Brum, Pedro Paulo Valadares, Lacerda, Anı́sio, and Pappa, Gisele L.
    In 7th Brazilian Conference on Intelligent Systems, BRACIS 2018, São Paulo, Brazil, October 22-25, 2018 2018
  3. Multi-objective Evolutionary Rank Aggregation for Recommender Systems
    Oliveira, Samuel E. L., Diniz, Victor, Lacerda, Anı́sio, and Pappa, Gisele L.
    In 2018 IEEE Congress on Evolutionary Computation, CEC 2018, Rio de Janeiro, Brazil, July 8-13, 2018 2018
  4. User-Oriented Objective Prioritization for Meta-Featured Multi-Objective Recommender Systems
    Fortes, Reinaldo Silva, Lacerda, Anı́sio, Freitas, Alan R. R., Bruckner, Carlos, Coelho, Dayanne, and Gonçalves, Marcos André
    In Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization, UMAP 2018, Singapore, July 08-11, 2018 2018

2017

  1. Multi-Objective Ranked Bandits for Recommender Systems
    Lacerda, Anı́sio
    Neurocomputing 2017
  2. A general framework to expand short text for topic modeling
    Bicalho, Paulo Viana, Pita, Marcelo, Pedrosa, Gabriel, Lacerda, Anı́sio, and Pappa, Gisele L.
    Inf. Sci. 2017
  3. A video summarization approach based on the emulation of bottom-up mechanisms of visual attention
    Jacob, Hugo, Pádua, Flávio L. C., Lacerda, Anı́sio, and Pereira, Adriano C. M.
    J. Intell. Inf. Syst. 2017
  4. A Robust Indoor Scene Recognition Method Based on Sparse Representation
    Nascimento, Guilherme, Laranjeira, Camila, Braz, Vinicius, Lacerda, Anı́sio, and Nascimento, Erickson R.
    In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 22nd Iberoamerican Congress, CIARP 2017, Valparaı́so, Chile, November 7-10, 2017, Proceedings 2017
  5. A Majority Voting Approach for Sentiment Analysis in Short Texts using Topic Models
    Carmo, Rodrigo Rodrigues, Lacerda, Anı́sio Mendes, and Dalip, Daniel Hasan
    In Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, Webmedia 2017, Gramado, Brazil, October 17 - 20, 2017 2017
  6. A Robust Indoor Scene Recognition Method based on Sparse Representation
    Nascimento, Guilherme, Laranjeira, Camila, Braz, Vinicius, Lacerda, Anı́sio, and Nascimento, Erickson R.
    CoRR 2017

2016

  1. Automatic and online setting of similarity thresholds in content-based visual information retrieval problems
    Bessas, Izaquiel L., Pádua, Flávio L. C., Assis, Guilherme T., Cardoso, Rodrigo T. N., and Lacerda, Anı́sio
    EURASIP J. Adv. Signal Process. 2016
  2. Topic Modeling for Short Texts with Co-occurrence Frequency-Based Expansion
    Pedrosa, Gabriel, Pita, Marcelo, Bicalho, Paulo Viana, Lacerda, Anı́sio, and Pappa, Gisele L.
    In 5th Brazilian Conference on Intelligent Systems, BRACIS 2016, Recife, Brazil, October 9-12, 2016 2016
  3. Evolutionary rank aggregation for recommender systems
    Oliveira, Samuel E. L., Diniz, Victor, Lacerda, Anı́sio, and Pappa, Gisele L.
    In IEEE Congress on Evolutionary Computation, CEC 2016, Vancouver, BC, Canada, July 24-29, 2016 2016

2015

  1. Improving daily deals recommendation using explore-then-exploit strategies
    Lacerda, Anı́sio, Santos, Rodrygo L. T., Veloso, Adriano, and Ziviani, Nivio
    Inf. Retr. J. 2015
  2. Contextual Bandits for Multi-objective Recommender Systems
    Lacerda, Anı́sio
    In 2015 Brazilian Conference on Intelligent Systems, BRACIS 2015, Natal, Brazil, November 4-7, 2015 2015
  3. Adding Value to Daily-Deals Recommendation: Multi-armed Bandits to Match Customers and Deals
    Lacerda, Anı́sio, Veloso, Adriano, and Ziviani, Nivio
    In 2015 Brazilian Conference on Intelligent Systems, BRACIS 2015, Natal, Brazil, November 4-7, 2015 2015
  4. MeGASS: Multi-Objective Genetic Active Site Search
    Izidoro, Sandro C., Lacerda, Anı́sio M., and Pappa, Gisele L.
    In Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, Companion Material Proceedings 2015

2014

  1. Multiobjective Pareto-Efficient Approaches for Recommender Systems
    Ribeiro, Marco Túlio, Ziviani, Nivio, Moura, Edleno Silva, Hata, Itamar, Lacerda, Anı́sio, and Veloso, Adriano
    ACM Trans. Intell. Syst. Technol. 2014
  2. Where Should I Go? City Recommendation Based on User Communities
    Bidart, Ruhan, Pereira, Adriano César Machado, Almeida, Jussara M., and Lacerda, Anı́sio
    In 9th Latin American Web Congress, LA-WEB 2014, Ouro Preto, Minas Gerais, Brazil, 22-24 October, 2014 2014
  3. Information-Theoretic Term Selection for New Item Recommendation
    Costa, Thales F., Lacerda, Anı́sio, Santos, Rodrygo L. T., and Ziviani, Nivio
    In String Processing and Information Retrieval - 21st International Symposium, SPIRE 2014, Ouro Preto, Brazil, October 20-22, 2014. Proceedings 2014
  4. Context-Aware Deal Size Prediction
    Lacerda, Anı́sio, Veloso, Adriano, Santos, Rodrygo L. T., and Ziviani, Nivio
    In String Processing and Information Retrieval - 21st International Symposium, SPIRE 2014, Ouro Preto, Brazil, October 20-22, 2014. Proceedings 2014

2013

  1. Revenue optimization and customer targeting in daily-deals sites
    Lacerda, Anı́sio M.
    2013
  2. GUARD: A Genetic Unified Approach for Recommendation
    Guimarães, Adolfo P., Costa, Thales F., Lacerda, Anı́sio, Pappa, Gisele L., and Ziviani, Nivio
    J. Inf. Data Manag. 2013
  3. Exploratory and interactive daily deals recommendation
    Lacerda, Anı́sio, Veloso, Adriano, and Ziviani, Nivio
    In Seventh ACM Conference on Recommender Systems, RecSys ’13, Hong Kong, China, October 12-16, 2013 2013
  4. Building user profiles to improve user experience in recommender systems
    Lacerda, Anı́sio, and Ziviani, Nivio
    In Sixth ACM International Conference on Web Search and Data Mining, WSDM 2013, Rome, Italy, February 4-8, 2013 2013
  5. Weighted slope one predictors revisited
    Menezes, Danilo, Lacerda, Anı́sio, Silva, Leila, Veloso, Adriano, and Ziviani, Nivio
    In 22nd International World Wide Web Conference, WWW ’13, Rio de Janeiro, Brazil, May 13-17, 2013, Companion Volume 2013

2012

  1. Using Taxonomies for Product Recommendation
    Matos-Junior, Osvaldo, Ziviani, Nivio, Botelho, Fabiano C., Cristo, Marco, Lacerda, Anı́sio, and Silva, Altigran Soares
    J. Inf. Data Manag. 2012
  2. Pareto-efficient hybridization for multi-objective recommender systems
    Ribeiro, Marco Túlio, Lacerda, Anı́sio, Veloso, Adriano, and Ziviani, Nivio
    In Sixth ACM Conference on Recommender Systems, RecSys ’12, Dublin, Ireland, September 9-13, 2012 2012

2011

  1. Minimal perfect hashing: A competitive method for indexing internal memory
    Botelho, Fabiano C., Lacerda, Anı́sio, Menezes, Guilherme Vale, and Ziviani, Nivio
    Inf. Sci. 2011

2010

  1. Demand-Driven Tag Recommendation
    Menezes, Guilherme Vale, Almeida, Jussara M., Belém, Fabiano, Gonçalves, Marcos André, Lacerda, Anı́sio, Moura, Edleno Silva, Pappa, Gisele L., Veloso, Adriano, and Ziviani, Nivio
    In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part II 2010

2006

  1. Learning to advertise
    Lacerda, Anı́sio, Cristo, Marco, Gonçalves, Marcos André, Fan, Weiguo, Ziviani, Nivio, and Ribeiro-Neto, Berthier A.
    In SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Seattle, Washington, USA, August 6-11, 2006 2006