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Eduardo R. Hruschka

Eduardo R. Hruschka

D-Index & Metrics

Computer Science

D-Index
32
Citations
6115
World Ranking
12966
National Ranking
62

Overview

Eduardo R. Hruschka is affiliated with the Universidade de São Paulo in Brazil. Their research focuses primarily on the field of Computer Science, with a specialization in Artificial Intelligence.

The main topics of their work include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Speech and dialogue systems

Eduardo R. Hruschka has contributed to academic publications through the following paper:

  • Contextualised Word Embeddings Based on Transfer Learning to Dialogue Response Generation: a Proposal and Comparisons (2021), published at the 2021 International Symposium on Electrical, Electronics and Information Engineering

Frequent co-authors collaborating with Eduardo R. Hruschka include:

  • Thomaz Calasans
  • Anna Helena Reali Costa

In terms of publication venues, Eduardo R. Hruschka's work appears in the following:

  • 2021 International Symposium on Electrical, Electronics and Information Engineering

Their research engages with advanced computational techniques for language understanding and generation, particularly focusing on dialogue systems and topic modeling approaches within artificial intelligence. The work explores the application of transfer learning and contextual embeddings to improve natural language processing tasks.

Best Publications

  • A Survey of Evolutionary Algorithms for Clustering

    E.R. Hruschka;R.J.G.B. Campello;A.A. Freitas;A.C.P.L.F. de Carvalho

  • Data stream clustering: A survey

    Jonathan A. Silva;Elaine R. Faria;Rodrigo C. Barros;Eduardo R. Hruschka

  • Tweet sentiment analysis with classifier ensembles

    Nádia F.F. da Silva;Eduardo R. Hruschka;Estevam R. Hruschka

  • A fuzzy extension of the silhouette width criterion for cluster analysis

    Ricardo J. G. B. Campello;Eduardo R. Hruschka

  • Relative clustering validity criteria: A comparative overview

    Lucas Vendramin;Ricardo J. G. B. Campello;Eduardo R. Hruschka

  • Relative clustering validity criteria: A comparative overview: Relative Clustering Validity Criteria

    Lucas Vendramin;Ricardo J. G. B. Campello;Eduardo R. Hruschka

  • Evolving clusters in gene-expression data

    Eduardo R. Hruschka;Ricardo J. G. B. Campello;Leandro N. de Castro

  • A genetic algorithm for cluster analysis

    Eduardo R. Hruschka;Nelson F. f. Ebecken

  • Simultaneous co-clustering and learning to address the cold start problem in recommender systems

    Andre Luiz Vizine Pereira;Eduardo Raul Hruschka

  • On the Comparison of Relative Clustering Validity Criteria.

    Lucas Vendramin;Ricardo J. G. B. Campello;Eduardo R. Hruschka

  • Efficiency issues of evolutionary k-means

    M. C. Naldi;R. J. G. B. Campello;E. R. Hruschka;A. C. P. L. F. Carvalho

  • Document Clustering for Forensic Analysis: An Approach for Improving Computer Inspection

    L. F. da Cruz Nassif;E. R. Hruschka

  • An evolutionary algorithm for clustering data streams with a variable number of clusters

    Jonathan de Andrade Silva;Eduardo Raul Hruschka;João Gama

  • Combining Classification and Clustering for Tweet Sentiment Analysis

    Luiz Fernando Sommaggio Coletta;Nadia Felix Felipe da Silva;Eduardo Raul Hruschka;Estevam Rafael Hruschka

  • Collaborative Fuzzy Clustering Algorithms: Some Refinements and Design Guidelines

    L. F. S. Coletta;L. Vendramin;E. R. Hruschka;R. J. G. B. Campello

  • A Survey and Comparative Study of Tweet Sentiment Analysis via Semi-Supervised Learning

    Nadia Felix F. Da Silva;Luiz F. S. Coletta;Eduardo R. Hruschka

  • Evolutionary algorithms for clustering gene-expression data

    E.R. Hruschka;L.N. de Castro;R.J.G.B. Campello

  • EXTRACTING RULES FROM MULTILAYER PERCEPTRONS IN CLASSIFICATION PROBLEMS: A CLUSTERING-BASED APPROACH

    Eduardo R. Hruschka;Nelson F.F. Ebecken

  • Bayesian networks for imputation in classification problems

    Estevam R. Hruschka;Eduardo R. Hruschka;Nelson F. Ebecken

  • Using unsupervised information to improve semi-supervised tweet sentiment classification

    Nádia Félix Felipe da Silva;Luiz F.S. Coletta;Eduardo R. Hruschka;Estevam R. Hruschka

  • Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem

    Jorge Kanda;Andre de Carvalho;Eduardo Hruschka;Carlos Soares

Frequent Co-Authors

Ricardo J. G. B. Campello
Ricardo J. G. B. Campello University of Southern Denmark
Joydeep Ghosh
Joydeep Ghosh The University of Texas at Austin
André C. P. L. F. de Carvalho
André C. P. L. F. de Carvalho Universidade de São Paulo
Leandro Nunes de Castro
Leandro Nunes de Castro Florida Gulf Coast University
João Gama
João Gama University of Porto
Witold Pedrycz
Witold Pedrycz University of Alberta
Alex A. Freitas
Alex A. Freitas University of Kent
Wagner Meira
Wagner Meira Universidade Federal de Minas Gerais
Raymond J. Mooney
Raymond J. Mooney The University of Texas at Austin

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