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Anísio Lacerda
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2020 – today
- 2024
- [j20]Michele A. Brandão, Arthur P. G. Reis, Bárbara M. A. Mendes, Clara A. Bacha, Gabriel P. Oliveira
, Henrique R. Hott
PLUS: A Semi-automated Pipeline for Fraud Detection in Public Bids. Digit. Gov. Res. Pract. 5(1): 5:1-5:16 (2024) - [j19]Mariana O. Silva
Overpricing Analysis in Brazilian Public Bidding Items. J. Interact. Syst. 15(1): 130-142 (2024) - [j18]Camila Santana Braz
Exploring Irregularities in Brazilian Public Bids: An In-depth Analysis on Small Companies. J. Interact. Syst. 15(1): 349-361 (2024) - [c32]Pedro Paulo Valadares Brum, Mariana O. Silva, Gabriel P. Oliveira, Lucas G. L. Costa, Anísio Lacerda, Gisele L. Pappa:
Unsupervised Grouping of Public Procurement Similar Items: Which Text Representation Should I Use? LREC/COLING 2024: 17176-17185 - 2023
- [j17]Gabriel P. Oliveira
Assessing Data Quality Inconsistencies in Brazilian Governmental Data. J. Inf. Data Manag. 14(1) (2023) - [c31]Henrique R. Hott
Evaluating Contextualized Embeddings for Topic Modeling in Public Bidding Domain. BRACIS (3) 2023: 410-426 - [c30]Anísio Lacerda, Claudio Almeida, Leonardo Augusto Ferreira, Adriano C. M. Pereira
Algorithmic Recourse in Mental Healthcare. IJCNN 2023: 1-8 - [c29]Anísio Lacerda, Daniel Ayala, Francisco Malaguth, Fabio Kanadani:
An Empirical Analysis of Vision Transformers Robustness to Spurious Correlations in Health Data. IJCNN 2023: 1-8 - [c28]Michele A. Brandão, Mariana O. Silva, Gabriel P. Oliveira, Henrique R. Hott, Anísio M. Lacerda, Gisele L. Pappa:
Impacto do Pré-processamento e Representação Textual na Classificação de Documentos de Licitações. SBBD 2023: 102-114 - [c27]Larissa D. Gomide, Guilherme Bezerra dos Santos, Lucas L. Costa, Michele A. Brandão, Anísio Lacerda, Gisele L. Pappa:
Mineração de Dados sobre Despesas Públicas de Municípios Mineiros para Gerar Alertas de Fraudes. SBBD 2023: 378-383 - 2022
- [j16]Guilherme F. Marchezini, Anísio M. Lacerda, Gisele L. Pappa
Counterfactual inference with latent variable and its application in mental health care. Data Min. Knowl. Discov. 36(2): 811-840 (2022) - [j15]Renato Miranda Filho
Explainable Regression Via Prototypes. ACM Trans. Evol. Learn. Optim. 2(4): 14:1-14:26 (2022) - [c26]Gabriel P. Oliveira
Ferramentas open-source de qualidade de dados para licitações públicas: Uma análise comparativa. SBBD 2022: 116-127 - [c25]Mariana O. Silva, Gabriel P. Oliveira
Collaboration as a Driving Factor for Hit Song Classification. WebMedia 2022: 66-74 - [c24]Gabriel P. Oliveira
Detecting Inconsistencies in Public Bids: An Automated and Data-based Approach. WebMedia 2022: 182-190 - 2021
- [j14]Reinaldo Silva Fortes
Individualized extreme dominance (IndED): A new preference-based method for multi-objective recommender systems. Inf. Sci. 572: 558-573 (2021) - [c23]Anísio Lacerda, Gisele L. Pappa:
Deep Thompson Sampling for Length of Stay Prediction. IJCNN 2021: 1-7 - 2020
- [j13]Samuel E. L. Oliveira
Is Rank Aggregation Effective in Recommender Systems? An Experimental Analysis. ACM Trans. Intell. Syst. Technol. 11(2): 16:1-16:26 (2020) - [c22]Renato Miranda Filho, Anísio Lacerda, Gisele L. Pappa:
Explaining Symbolic Regression Predictions. CEC 2020: 1-8 - [c21]Gabriel P. Oliveira, Mariana Santos, Danilo B. Seufitelli, Anísio Lacerda, Mirella M. Moro:
Detecting Collaboration Profiles in Success-based Music Genre Networks. ISMIR 2020: 726-732
2010 – 2019
- 2019
- [j12]Felipe L. A. Conceiç ao, Flávio L. C. Pádua, Anísio Lacerda, Adriano César Machado Pereira, Daniel Hasan Dalip
Multimodal data fusion framework based on autoencoders for top-N recommender systems. Appl. Intell. 49(9): 3267-3282 (2019) - [j11]Moisés H. R. Pereira
Multimodal approach for tension levels estimation in news videos. Multim. Tools Appl. 78(16): 23783-23808 (2019) - [c20]Camila Laranjeira, Anísio Lacerda, Erickson R. Nascimento:
On Modeling Context from Objects with a Long Short-Term Memory for Indoor Scene Recognition. SIBGRAPI 2019: 249-256 - 2018
- [j10]Celso Luiz de Souza
A computational approach to support the creation of terminological neologisms in sign languages. Comput. Appl. Eng. Educ. 26(3): 517-530 (2018) - [c19]Samuel E. L. Oliveira, Pedro Paulo Valadares Brum, Anísio Lacerda, Gisele L. Pappa:
Exploiting Multiple Recommenders to Improve Group Recommendation. BRACIS 2018: 324-329 - [c18]Samuel E. L. Oliveira, Victor Diniz, Anísio Lacerda, Gisele L. Pappa:
Multi-objective Evolutionary Rank Aggregation for Recommender Systems. CEC 2018: 1-8 - [c17]Reinaldo Silva Fortes
User-Oriented Objective Prioritization for Meta-Featured Multi-Objective Recommender Systems. UMAP (Adjunct Publication) 2018: 311-316 - 2017
- [j9]Anísio Lacerda:
Multi-Objective Ranked Bandits for Recommender Systems. Neurocomputing 246: 12-24 (2017) - [j8]Paulo Viana Bicalho, Marcelo Pita, Gabriel Pedrosa, Anísio Lacerda, Gisele L. Pappa:
A general framework to expand short text for topic modeling. Inf. Sci. 393: 66-81 (2017) - [j7]Hugo Jacob, Flávio L. C. Pádua, Anísio Lacerda, Adriano C. M. Pereira
A video summarization approach based on the emulation of bottom-up mechanisms of visual attention. J. Intell. Inf. Syst. 49(2): 193-211 (2017) - [c16]Guilherme Nascimento
A Robust Indoor Scene Recognition Method Based on Sparse Representation. CIARP 2017: 408-415 - [c15]Rodrigo Rodrigues do Carmo, Anísio Mendes Lacerda, Daniel Hasan Dalip:
A Majority Voting Approach for Sentiment Analysis in Short Texts using Topic Models. WebMedia 2017: 449-455 - [i1]Guilherme Nascimento, Camila Laranjeira, Vinicius Braz, Anísio Lacerda, Erickson R. Nascimento:
A Robust Indoor Scene Recognition Method based on Sparse Representation. CoRR abs/1708.07555 (2017) - 2016
- [j6]Izaquiel L. Bessas, Flávio L. C. Pádua, Guilherme T. de Assis, Rodrigo T. N. Cardoso
Automatic and online setting of similarity thresholds in content-based visual information retrieval problems. EURASIP J. Adv. Signal Process. 2016: 32 (2016) - [c14]Gabriel Pedrosa, Marcelo Pita, Paulo Viana Bicalho, Anísio Lacerda, Gisele L. Pappa:
Topic Modeling for Short Texts with Co-occurrence Frequency-Based Expansion. BRACIS 2016: 277-282 - [c13]Samuel E. L. Oliveira, Victor Diniz, Anísio Lacerda, Gisele L. Pappa:
Evolutionary rank aggregation for recommender systems. CEC 2016: 255-262 - 2015
- [j5]Anísio Lacerda, Rodrygo L. T. Santos
Improving daily deals recommendation using explore-then-exploit strategies. Inf. Retr. J. 18(2): 95-122 (2015) - [c12]Anísio Lacerda:
Contextual Bandits for Multi-objective Recommender Systems. BRACIS 2015: 68-73 - [c11]Anísio Lacerda, Adriano Veloso, Nivio Ziviani:
Adding Value to Daily-Deals Recommendation: Multi-armed Bandits to Match Customers and Deals. BRACIS 2015: 216-221 - [c10]Sandro C. Izidoro
MeGASS: Multi-Objective Genetic Active Site Search. GECCO (Companion) 2015: 905-910 - 2014
- [j4]Marco Túlio Ribeiro, Nivio Ziviani, Edleno Silva de Moura, Itamar Hata, Anísio Lacerda, Adriano Veloso:
Multiobjective Pareto-Efficient Approaches for Recommender Systems. ACM Trans. Intell. Syst. Technol. 5(4): 53:1-53:20 (2014) - [c9]Ruhan Bidart, Adriano César Machado Pereira
Where Should I Go? City Recommendation Based on User Communities. LA-WEB 2014: 50-58 - [c8]Thales F. Costa, Anísio Lacerda, Rodrygo L. T. Santos
Information-Theoretic Term Selection for New Item Recommendation. SPIRE 2014: 236-243 - [c7]Anísio Lacerda, Adriano Veloso, Rodrygo L. T. Santos
Context-Aware Deal Size Prediction. SPIRE 2014: 256-267 - 2013
- [b1]Anísio M. Lacerda:
Revenue optimization and customer targeting in daily-deals sites. Federal University of Minas Gerais, Brazil, 2013 - [j3]Adolfo P. Guimarães, Thales F. Costa, Anísio Lacerda, Gisele L. Pappa, Nivio Ziviani:
GUARD: A Genetic Unified Approach for Recommendation. J. Inf. Data Manag. 4(3): 295-310 (2013) - [c6]Anísio Lacerda, Adriano Veloso, Nivio Ziviani:
Exploratory and interactive daily deals recommendation. RecSys 2013: 439-442 - [c5]Anísio Lacerda, Nivio Ziviani:
Building user profiles to improve user experience in recommender systems. WSDM 2013: 759-764 - [c4]Danilo Menezes, Anísio Lacerda, Leila Silva, Adriano Veloso, Nivio Ziviani:
Weighted slope one predictors revisited. WWW (Companion Volume) 2013: 967-972 - 2012
- [j2]Osvaldo Matos-Junior, Nivio Ziviani, Fabiano C. Botelho, Marco Cristo, Anísio Lacerda, Altigran Soares da Silva:
Using Taxonomies for Product Recommendation. J. Inf. Data Manag. 3(2): 85-100 (2012) - [c3]Marco Túlio Ribeiro, Anísio Lacerda, Adriano Veloso, Nivio Ziviani:
Pareto-efficient hybridization for multi-objective recommender systems. RecSys 2012: 19-26 - 2011
- [j1]Fabiano C. Botelho, Anísio Lacerda, Guilherme Vale Menezes, Nivio Ziviani:
Minimal perfect hashing: A competitive method for indexing internal memory. Inf. Sci. 181(13): 2608-2625 (2011) - 2010
- [c2]Guilherme Vale Menezes, Jussara M. Almeida, Fabiano Belém, Marcos André Gonçalves
Demand-Driven Tag Recommendation. ECML/PKDD (2) 2010: 402-417
2000 – 2009
- 2006
- [c1]Anísio Lacerda, Marco Cristo, Marcos André Gonçalves, Weiguo Fan, Nivio Ziviani, Berthier A. Ribeiro-Neto:
Learning to advertise. SIGIR 2006: 549-556
Coauthor Index
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last updated on 2024-10-07 21:21 CEST by the dblp team
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