Estevam R. Hruschka Jr.

Publication Activity (10 Years)

Years Active: 2002-2020
Publications (10 Years): 13

Top Topics

Sentiment Analysis

Temporal Relations

Bayesian Networks

Coreference Resolution

Top Venues

Fundam. Informaticae

Publications

Estevam R. Hruschka Jr.
Data-Driven Never-Ending Learning Question Answering Systems. KDD (2020)
Edimilson Batista dos Santos, Igor Henrique P. Rodrigues, Estevam R. Hruschka Jr., Lucas Rezende Bruno
Bayesian Networks for Inference and Discovery of Semantic Relations in a Never-Ending Learning System. BRACIS (2019)
Daniel Severo, Flávio Amaro, Estevam R. Hruschka Jr., André Soares de Moura Costa
Ward2ICU: A Vital Signs Dataset of Inpatients from the General Ward. CoRR (2019)
Saulo D. de S. Pedro, Estevam R. Hruschka Jr.
Crowd-Powered Systems to Diminish the Effects of Semantic Drift. HAIS (2019)
Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha P. Talukdar, Bo Yang, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling
Never-ending learning. Commun. ACM 61 (5) (2018)
José M. Giménez-García, Maísa Cristina Duarte, Antoine Zimmermann, Christophe Gravier, Estevam R. Hruschka Jr., Pierre Maret
NELL2RDF: Reading the Web, Tracking the Provenance, and Publishing it as Linked Data. CKGSemStats@ISWC (2018)
José M. Giménez-García, Maisa C. Duarte, Antoine Zimmermann, Christophe Gravier, Estevam R. Hruschka Jr., Pierre Maret
NELL2RDF: Reading the Web, and Publishing it as Linked Data. CoRR (2018)
Jerónimo Hernández-González, Estevam R. Hruschka Jr., Tom M. Mitchell
Merging knowledge bases in different languages. TextGraphs@ACL (2017)
Stefano V. Albrecht, Bruno Bouchard, John S. Brownstein, David L. Buckeridge, Cornelia Caragea, Kevin M. Carter, Adnan Darwiche, Blaz Fortuna, Yannick Francillette, Sébastien Gaboury, C. Lee Giles, Marko Grobelnik, Estevam R. Hruschka Jr., Jeffrey O. Kephart, Parisa Kordjamshidi, Viliam Lisý, Daniele Magazzeni, João Marques-Silva, Pierre Marquis, David R. Martinez, Marek P. Michalowski, Arash Shaban-Nejad, Zeinab Noorian, Enrico Pontelli, Alex Rogers, Stephanie Rosenthal, Dan Roth, Arunesh Sinha, William W. Streilein, Sylvie Thiébaux, Tran Cao Son, Byron C. Wallace, Toby Walsh, Michael J. Witbrock, Jie Zhang
Reports of the 2016 AAAI Workshop Program. AI Mag. 37 (3) (2016)
Edimilson Batista dos Santos, Massilon Lourenço Fernandes, Estevam R. Hruschka Jr., Maísa Cristina Duarte
Bayesian Networks for Identifying Semantic Relations in a Never-Ending Learning System. ISDA (2016)
Lucas Fonseca Navarro, Estevam R. Hruschka Jr., Ana Paula Appel
Finding Inference Rules Using Graph Mining in Ontological Knowledge Bases. BRACIS (2016)
Zhiyuan Chen, Estevam R. Hruschka Jr., Bing Liu
Lifelong Machine Learning and Computer Reading the Web. KDD (2016)
Nádia Félix Felipe da Silva, Luiz F. S. Coletta, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Using unsupervised information to improve semi-supervised tweet sentiment classification. Inf. Sci. (2016)
Dunja Mladenic, Estevam R. Hruschka Jr., Marko Grobelnik
Editorial. J. Web Semant. 35 (2015)
Tom M. Mitchell, William W. Cohen, Estevam R. Hruschka Jr., Partha Pratim Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi Mishra, Matthew Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapandula Nakashole, Emmanouil A. Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard C. Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcolm Greaves, Joel Welling
Never-Ending Learning. AAAI (2015)
Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.
Transgenic: An evolutionary algorithm operator. Neurocomputing 127 (2014)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Nelson F. F. Ebecken
The influences of canonical evolutionary algorithm operators and variable orderings in learning Bayesian classifiers from data. Int. J. Hybrid Intell. Syst. 11 (3) (2014)
Maisa C. Duarte, Estevam R. Hruschka Jr.
Exploring two views of coreference resolution in a never-ending learning system. HIS (2014)
Nádia Félix F. da Silva, Estevam R. Hruschka Jr., Eduardo R. Hruschka
Biocom_Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble. SemEval@COLING (2014)
Maisa C. Duarte, Estevam R. Hruschka Jr.
How to read the web in portuguese using the never-ending language learner's principles. ISDA (2014)
Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Tweet sentiment analysis with classifier ensembles. Decis. Support Syst. 66 (2014)
Luiz Fernando Sommaggio Coletta, Nádia Félix F. da Silva, Eduardo R. Hruschka, Estevam R. Hruschka Jr.
Combining Classification and Clustering for Tweet Sentiment Analysis. BRACIS (2014)
Estevam R. Hruschka Jr., Maisa C. Duarte, Maria C. Nicoletti
Coupling as Strategy for Reducing Concept-Drift in Never-ending Learning Environments. Fundam. Informaticae 124 (1-2) (2013)
Saulo D. de S. Pedro, Ana Paula Appel, Estevam R. Hruschka Jr.
Autonomously reviewing and validating the knowledge base of a never-ending learning system. WWW (Companion Volume) (2013)
Maria C. Nicoletti, Flávia O. Santos de Sá Lisboa, Estevam R. Hruschka Jr.
Automatic Learning of Temporal Relations Under the Closed World Assumption. Fundam. Informaticae 124 (1-2) (2013)
Vinicius Oliverio, Estevam R. Hruschka Jr.
Contradiction Detection and Ontology Extension in a Never-Ending Learning System. IBERAMIA (2012)
Saurabh Verma, Estevam R. Hruschka Jr.
Coupled Bayesian Sets Algorithm for Semi-supervised Learning and Information Extraction. ECML/PKDD (2) (2012)
Saulo D. de S. Pedro, Estevam R. Hruschka Jr.
Collective intelligence as a source for machine learning self-supervision. WI&C (2012)
Saulo D. de S. Pedro, Estevam R. Hruschka Jr.
Conversing Learning: Active Learning and Active Social Interaction for Human Supervision in Never-Ending Learning Systems. IBERAMIA (2012)
Maria C. Nicoletti, Flávia O. Santos de Sá Lisboa, Estevam R. Hruschka Jr., Osvaldo Luiz De Oliveira
Representation and automatic learning of temporal relations between time periods with uncertain boundaries. ISDA (2012)
Maísa Cristina Duarte, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Minimização do Impacto do Problema de Desvio de Conceito por Meio de Acoplamento em Ambiente de Aprendizado Sem Fim (Minimizing the Impact of the Concept Drift Problem by Using a Framework of Endless Learning) [in Portuguese]. STIL (2011)
Edimilson Batista dos Santos, Nelson F. F. Ebecken, Estevam R. Hruschka Jr.
Learning Bayesian Network structures using Multiple Offspring Sampling. ISDA (2011)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Bayesian network classifiers: Beyond classification accuracy. Intell. Data Anal. 15 (3) (2011)
Thahir Mohamed, Estevam R. Hruschka Jr., Tom M. Mitchell
Discovering Relations between Noun Categories. EMNLP (2011)
Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.
Transgenic, an operator for evolutionary algorithms. IEEE Congress on Evolutionary Computation (2011)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Bayesian imputation method for a clustering genetic algorithm. J. Comput. Methods Sci. Eng. 11 (4) (2011)
Laurence Rodrigues do Amaral, Estevam R. Hruschka Jr.
Gene ontology classification: Building high-level knowledge using genetic algorithms. IEEE Congress on Evolutionary Computation (2010)
Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R. Hruschka Jr., Tom M. Mitchell
Toward an Architecture for Never-Ending Language Learning. AAAI (2010)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Distance-Based Mutation Operator for learning Bayesian Network structures using Evolutionary Algorithms. IEEE Congress on Evolutionary Computation (2010)
Andrew Carlson, Justin Betteridge, Richard C. Wang, Estevam R. Hruschka Jr., Tom M. Mitchell
Coupled semi-supervised learning for information extraction. WSDM (2010)
Ana Paula Appel, Estevam R. Hruschka Jr.
Centaurs - A Component-based Framework to Mine Large Graphs. SBBD (Posters) (2010)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Evolutionary Algorithm Using Random Multi-point Crossover Operator for Learning Bayesian Network Structures. ICMLA (2010)
I-Hsien Yin, Estevam R. Hruschka Jr., Heloisa de Arruda Camargo
Intelligent Classification System Using a Pruned Bayes Fuzzy Rule Set. ICMLA (2010)
I-Hsien Yin, Estevam R. Hruschka Jr., Heloisa de Arruda Camargo
The Impact of Pruning BayesFuzzy Rule Set. ISDA (2009)
Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam R. Hruschka Jr., Richard C. Wang
Populating the Semantic Web by Macro-reading Internet Text. ISWC (2009)
Eduardo R. Hruschka, Antonio J. T. Garcia, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
On the influence of imputation in classification: practical issues. J. Exp. Theor. Artif. Intell. 21 (1) (2009)
Gláucia M. Bressan, Vilma A. de Oliveira, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop. Eng. Appl. Artif. Intell. 22 (4-5) (2009)
Justin Betteridge, Andrew Carlson, Sue Ann Hong, Estevam R. Hruschka Jr., Edith L. M. Law, Tom M. Mitchell, Sophie H. Wang
Toward Never Ending Language Learning. AAAI Spring Symposium: Learning by Reading and Learning to Read (2009)
Marcos Evandro Cintra, Heloisa de Arruda Camargo, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Automatic Construction of Fuzzy Rule Bases: a further Investigation into two Alternative Inductive Approaches. J. Univers. Comput. Sci. 14 (15) (2008)
Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Vilma A. de Oliveira, Gláucia M. Bressan
BayesRule: A Markov-Blanket based procedure for extracting a set of probabilistic rules from Bayesian classifiers. Int. J. Hybrid Intell. Syst. 5 (2) (2008)
Maria do Carmo Nicoletti, Lucas Baggio Figueira, Estevam R. Hruschka Jr.
Transferring neural network based knowledge into an exemplar-based learner. Neural Comput. Appl. 16 (3) (2007)
Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Vilma A. de Oliveira, Gláucia M. Bressan
Markov-Blanket Based Strategy for Translating a Bayesian Classifier into a Reduced Set of Classification Rules. HIS (2007)
Diego P. Vivencio, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti, Edimilson Batista dos Santos, Sebastian D. C. de O. Galvão
Feature-weighted k-Nearest Neighbor Classifier. FOCI (2007)
Estevam R. Hruschka Jr., Heloisa de Arruda Camargo, Marcos Evandro Cintra, Maria do Carmo Nicoletti
BayesFuzzy: Using a Bayesian Classifier to Induce a Fuzzy Rule Base. FUZZ-IEEE (2007)
Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Towards efficient variables ordering for Bayesian networks classifier. Data Knowl. Eng. 63 (2) (2007)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Bayesian networks for imputation in classification problems. J. Intell. Inf. Syst. 29 (3) (2007)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Conditional independence based learning of bayesian classifiers guided by a variable ordering genetic search. IEEE Congress on Evolutionary Computation (2007)
Daniel Monegatto Santoro, Maria do Carmo Nicoletti, Estevam R. Hruschka Jr.
C-Focus-3: a C-Focus with a New Heuristic Search Strategy. ISDA (2007)
Estevam R. Hruschka Jr., Edimilson Batista dos Santos, Sebastian D. C. de O. Galvão
Variable Ordering in the Conditional Independence Bayesian Classifier Induction Process: An Evolutionary Approach. HIS (2007)
Sebastian D. C. de O. Galvão, Estevam R. Hruschka Jr.
A Markov Blanket Based Strategy to Optimize the Induction of Bayesian Classifiers When Using Conditional Independence Learning Algorithms. DaWaK (2007)
Estevam R. Hruschka Jr., Sebastian D. C. de O. Galvão
Fast Conditional Independence-based Bayesian Classifier. J. Comput. Sci. Eng. 1 (2) (2007)
Saul D. de S. S. Pedro, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
WNB: A Weighted Naïve Bayesian Classifier. ISDA (2007)
Marcos Evandro Cintra, Heloisa de Arruda Camargo, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Fuzzy Rule Base Generation through Genetic Algorithms and Bayesian Classifiers A Comparative Approach. ISDA (2007)
Gláucia M. Bressan, Vilma A. de Oliveira, Estevam R. Hruschka Jr., Maria C. Nicoletti
Biomass Based Weed-Crop Competitiveness Classification Using Bayesian Networks. ISDA (2007)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Estevam R. Hruschka Jr.
A Comparative Evaluation of Constructive Neural Networks Methods using PRM and BCP as TLU Training Algorithms. SMC (2006)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Thiago F. Covoes, Nelson F. F. Ebecken
Bayesian Feature Selection for Clustering Problems. J. Inf. Knowl. Manag. 5 (4) (2006)
Edimilson Batista dos Santos, Estevam R. Hruschka Jr.
VOGA: Variable Ordering Genetic Algorithm for Learning Bayesian Classifiers. HIS (2006)
João Roberto Bertini Jr., Maria do Carmo Nicoletti, Estevam R. Hruschka Jr., Arthur Ramer
Two Variants of the Constructive Neural Network Tiling Algorithm. HIS (2006)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Applying Bayesian Networks for Meteorological Data Mining. SGAI Conf. (Applications) (2005)
Eduardo R. Hruschka, Thiago F. Covoes, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Feature Selection for Clustering Problems: a Hybrid Algorithm that Iterates Between k-means and a Bayesian Filter. HIS (2005)
Daniel Monegatto Santoro, Estevam R. Hruschka Jr., Maria do Carmo Nicoletti
Selecting feature subsets for inducing classifiers using a committee of heterogeneous methods. SMC (2005)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Missing Values Imputation for a Clustering Genetic Algorithm. ICNC (3) (2005)
Maria do Carmo Nicoletti, Lucas Baggio Figueira, Estevam R. Hruschka Jr.
Initializing an Exemplar Based Learning Process from a RuleNet Network. HIS (2005)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
Feature Selection by Bayesian Networks. Canadian Conference on AI (2004)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Towards Efficient Imputation by Nearest-Neighbors: A Clustering-Based Approach. Australian Conference on Artificial Intelligence (2004)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Evaluating a Nearest-Neighbor Method to Substitute Continuous Missing Values. Australian Conference on Artificial Intelligence (2003)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Feature Selection Bayesian Approach for Extracting Classification Rules with a Clustering Genetic Algorithm. Appl. Artif. Intell. 17 (5-6) (2003)
Eduardo R. Hruschka, Estevam R. Hruschka Jr., Nelson F. F. Ebecken
A Nearest-Neighbor Method as a Data Preparation Tool for a Clustering Genetic Algorithm. SBBD (2003)
Estevam R. Hruschka Jr., Eduardo R. Hruschka, Nelson F. F. Ebecken
A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. HIS (2002)
Estevam R. Hruschka Jr., Nelson F. F. Ebecken
Missing values prediction with K2. Intell. Data Anal. 6 (6) (2002)