Marcelo G. Manzato

According to our database, Marcelo G. Manzato authored at least 71 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Digitally nudging users to explore off-profile recommendations: here be dragons.

Gabrielle Alves, Dietmar Jannach, Rodrigo Ferrari de Souza, Daniela E. Damian, Marcelo Garcia Manzato

User Model. User Adapt. Interact., April, 2024

Model-Agnostic Knowledge Graph Embedding Explanations for Recommender Systems.

André Levi Zanon, Leonardo Chaves Dutra da Rocha, Marcelo Garcia Manzato

Proceedings of the Explainable Artificial Intelligence, 2024

User Perception of Fairness-Calibrated Recommendations.

Gabrielle Alves, Dietmar Jannach, Rodrigo Ferrari de Souza, Marcelo Garcia Manzato

Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, 2024

2023

Offline Metrics for Evaluating Explanation Goals in Recommender Systems.

André Levi Zanon, Marcelo Garcia Manzato, Leonardo Rocha

CoRR, 2023

A User Study on Explanations with Different Levels of Detail in Recommender Systems.

Luan Soares de Souza, Marcelo Garcia Manzato

Proceedings of the 29th Brazilian Symposium on Multimedia and the Web, 2023

Counteracting Popularity-Bias and Improving Diversity Through Calibrated Recommendations.

Andre Sacilotti, Rodrigo Ferrari de Souza, Marcelo G. Manzato

Proceedings of the 25th International Conference on Enterprise Information Systems, 2023

2022

Extended recommendation-by-explanation.

Arpit Rana, Rafael Martins D'Addio, Marcelo G. Manzato, Derek Bridge

User Model. User Adapt. Interact., 2022

Balancing the trade-off between accuracy and diversity in recommender systems with personalized explanations based on Linked Open Data.

André L. Zanon, Leonardo Chaves Dutra da Rocha, Marcelo Garcia Manzato

Knowl. Based Syst., 2022

A user study with aspect-based sentiment analysis for similarity of items in content-based recommendations.

André L. Zanon, Luan Souza, Diany Pressato, Marcelo Garcia Manzato

Expert Syst. J. Knowl. Eng., 2022

Aspect-Based Summarization: An Approach With Different Levels of Details to Explain Recommendations.

Luan Soares de Souza, Marcelo Garcia Manzato

Proceedings of the WebMedia '22: Brazilian Symposium on Multimedia and Web, Curitiba, Brazil, November 7, 2022

Human-ChatBot Interaction: measuring the psychophysiological reactions of chatbot users.

Helen Santos Picoli, Cynthya Letícia Teles de Oliveira, Lucas Padilha M. De Oliveira, Marcelo G. Manzato, Kamila Rios da Hora Rodrigues

Proceedings of the WebMedia '22: Brazilian Symposium on Multimedia and Web, Curitiba, Brazil, November 7, 2022

Empirical Studies Aimed at Understanding Conversational Recommender Systems and Accessibility Aspects.

Lucas Padilha Modesto de Araujo, Cynthya Letícia Teles de Oliveira, Kamila Rios da Hora Rodrigues, Marcelo Garcia Manzato

Proceedings of the HCI International 2022 - Late Breaking Papers: HCI for Health, Well-being, Universal Access and Healthy Aging, 2022

2021

A comparison among keyframe extraction techniques for CNN classification based on video periocular images.

Carolina Toledo Ferraz, William Barcellos, Osmando Pereira Junior, Tamiris Trevisan Negri Borges, Marcelo Garcia Manzato, Adilson Gonzaga, José Hiroki Saito

Multim. Tools Appl., 2021

Exploiting personalized calibration and metrics for fairness recommendation.

Diego Corrêa da Silva, Marcelo Garcia Manzato, Frederico Araújo Durão

Expert Syst. Appl., 2021

An Interpretable Recommendation Model for Gerontological Care.

Andre Paulino de Lima, Laurentino Augusto Dantas, Marcelo Garcia Manzato, Maria da Graça Campos Pimentel, Brunela Della Maggiori Orlandi, Paula Castro

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

2020

Pre-processing approaches for collaborative filtering based on hierarchical clustering.

Fernando Soares de Aguiar Neto, Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Inf. Sci., 2020

WordRecommender: An Explainable Content-Based Algorithm based on Sentiment Analysis and Semantic Similarity.

André L. Zanon, Luan Souza, Diany Pressato, Marcelo G. Manzato

Proceedings of the WebMedia '20: Brazillian Symposium on Multimedia and the Web, São Luís, Brazil, November 30, 2020

2019

Combining different metadata views for better recommendation accuracy.

Rafael Martins D'Addio, Ronnie S. Marinho, Marcelo G. Manzato

Inf. Syst., 2019

Boosting collaborative filtering with an ensemble of co-trained recommenders.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Expert Syst. Appl., 2019

A personalized clustering-based approach using open linked data for search space reduction in recommender systems.

Arthur F. Da Costa, Rafael Martins D'Addio, Eduardo P. Fressato, Marcelo G. Manzato

Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, 2019

2018

CoBaR: Confidence-Based Recommender.

Fernando Soares de Aguiar Neto, Arthur F. Da Costa, Marcelo G. Manzato

CoRR, 2018

Incorporating Semantic Item Representations to Soften the Cold Start Problem.

Rafael Martins D'Addio, Eduardo P. Fressato, Arthur F. Da Costa, Marcelo G. Manzato

Proceedings of the 24th Brazilian Symposium on Multimedia and the Web, 2018

Evaluating Multiple User Interactions for Ranking Personalization Using Ensemble Methods.

Frederico Araújo Durão, Bruno Souza Cabral, Marcelo G. Manzato, Arthur F. Da Costa

Proceedings of the 30th International Conference on Software Engineering and Knowledge Engineering, 2018

CoRec: a co-training approach for recommender systems.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 33rd Annual ACM Symposium on Applied Computing, 2018

Case recommender: a flexible and extensible python framework for recommender systems.

Arthur F. Da Costa, Eduardo P. Fressato, Fernando Soares de Aguiar Neto, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

Similarity-Based Matrix Factorization for Item Cold-Start in Recommender Systems.

Eduardo Pereira Fressato, Arthur Fortes da Costa, Marcelo Garcia Manzato

Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017

Ensemble Clustering Approaches Applied in Group-based Collaborative Filtering Supported by Multiple Users' Feedback.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

J. Inf. Data Manag., 2017

Exploiting feature extraction techniques on users' reviews for movies recommendation.

Rafael Martins D'Addio, Marcos Aurélio Domingues, Marcelo G. Manzato

J. Braz. Comput. Soc., 2017

Semantic Organization of User's Reviews Applied in Recommender Systems.

Ronnie S. Marinho, Rafael Martins D'Addio, Marcelo G. Manzato

Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, 2017

Face Classification using a New Local Texture Descriptor.

Carolina Toledo Ferraz, Marcelo Garcia Manzato, Adilson Gonzaga

Proceedings of the 23rd Brazillian Symposium on Multimedia and the Web, 2017

2016

Exploiting multimodal interactions in recommender systems with ensemble algorithms.

Arthur F. Da Costa, Marcelo G. Manzato

Inf. Syst., 2016

Mining unstructured content for recommender systems: an ensemble approach.

Marcelo G. Manzato, Marcos Aurélio Domingues, Arthur da Costa Fortes, Camila Vaccari Sundermann, Rafael Martins D'Addio, Merley da Silva Conrado, Solange O. Rezende, Maria G. C. Pimentel

Inf. Retr. J., 2016

Exploiting Item Representations for Soft Clustering Recommendation.

Rafael Martins D'Addio, Marcelo G. Manzato

Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web, 2016

Group-based Collaborative Filtering Supported by Multiple Users' Feedback to Improve Personalized Ranking.

Arthur F. Da Costa, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 22nd Brazilian Symposium on Multimedia and the Web, 2016

Exploiting different users' interactions for profiles enrichment in recommender systems.

Arthur F. Da Costa, Rafael D. Martins, Marcelo G. Manzato, Ricardo J. G. B. Campello

Proceedings of the 31st Annual ACM Symposium on Applied Computing, 2016

2015

Leveraging Hybrid Recommenders with Multifaceted Implicit Feedback.

Marcelo G. Manzato, Edson B. Santos Junior, Rudinei Goularte

J. Univers. Comput. Sci., 2015

Collaborative Filtering Based on Semantic Distance Among Items.

Salmo M. S. Júnior, Marcelo G. Manzato

Proceedings of the 21st Brazilian Symposium on Multimedia and the Web, 2015

Applying multi-view based metadata in personalized ranking for recommender systems.

Marcos Aurélio Domingues, Camila Vaccari Sundermann, Flávio M. M. Barros, Marcelo G. Manzato, Maria G. C. Pimentel, Solange Oliveira Rezende

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

A sentiment-based item description approach for kNN collaborative filtering.

Rafael Martins D'Addio, Marcelo G. Manzato

Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015

Introducing the concept of "always-welcome recommendations".

Edson B. dos Santos, Arthur F. Da Costa, Rafael Martins D'Addio, Marcelo Garcia Manzato, Rudinei Goularte

Proceedings of the 14th IEEE/ACIS International Conference on Computer and Information Science, 2015

2014

Ensemble Learning in Recommender Systems: Combining Multiple User Interactions for Ranking Personalization.

Arthur da Costa Fortes, Marcelo Garcia Manzato

Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, 2014

Generating Recommendations Based on Robust Term Extraction from Users' Reviews.

Rafael Martins D'Addio, Merley Conrado, Solange O. Rezende, Marcelo Garcia Manzato

Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, 2014

Combining Multiple Metadata Types in Movies Recommendation Using Ensemble Algorithms.

Bruno Souza Cabral, Renato Dompieri Beltrao, Marcelo Garcia Manzato, Frederico Araújo Durão

Proceedings of the 20th Brazilian Symposium on Multimedia and the Web, 2014

Optimizing Personalized Ranking in Recommender Systems with Metadata Awareness.

Marcelo G. Manzato, Marcos Aurélio Domingues, Solange Oliveira Rezende

Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

Exploiting Text Mining Techniques for Contextual Recommendations.

Marcos Aurélio Domingues, Camila Vaccari Sundermann, Marcelo Garcia Manzato, Ricardo Marcondes Marcacini, Solange Oliveira Rezende

Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

Improving Personalized Ranking in Recommender Systems with Multimodal Interactions.

Arthur F. Da Costa, Marcos Aurélio Domingues, Solange Oliveira Rezende, Marcelo G. Manzato

Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

Personalized collaborative filtering: a neighborhood model based on contextual constraints.

Edson B. Santos Junior, Rudinei Goularte, Marcelo G. Manzato

Proceedings of the Symposium on Applied Computing, 2014

Improving Personalized Ranking in Recommender Systems with Topic Hierarchies and Implicit Feedback.

Marcelo Garcia Manzato, Marcos Aurélio Domingues, Ricardo Marcondes Marcacini, Solange Oliveira Rezende

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Using Contextual Information from Topic Hierarchies to Improve Context-Aware Recommender Systems.

Marcos Aurélio Domingues, Marcelo Garcia Manzato, Ricardo Marcondes Marcacini, Camila Vaccari Sundermann, Solange Oliveira Rezende

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Multimodal Interactions in Recommender Systems: An Ensembling Approach.

Arthur da Costa Fortes, Marcelo Garcia Manzato

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

A Collaborative Filtering Approach Based on User's Reviews.

Rafael Martins D'Addio, Marcelo Garcia Manzato

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

Evaluating the Combination of Multiple Metadata Types in Movies Recommendation.

Renato Dompieri Beltrao, Bruno Souza Cabral, Marcelo Garcia Manzato, Frederico Araújo Durão

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

A conceptual architecture with trust consensus to enhance group recommendations.

Edson B. Santos Junior, Marcelo G. Manzato, Rudinei Goularte

Proceedings of the 2014 IEEE/ACIS 13th International Conference on Computer and Information Science, 2014

2013

Hybrid recommenders: incorporating metadata awareness into latent factor models.

Edson B. Santos Junior, Marcelo G. Manzato, Rudinei Goularte

Proceedings of the 19th Brazilian Symposium on Multimedia and the Web, 2013

gSVD++: supporting implicit feedback on recommender systems with metadata awareness.

Marcelo Garcia Manzato

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

2012

Automatic annotation of tagged content using predefined semantic concepts.

Marcelo Garcia Manzato, Rudinei Goularte

Proceedings of the Brazilian Symposium on Multimedia and the Web, 2012

Accelerometers data interoperability: easing interactive applications development.

Jorge Rodrigues Carvalho, Marcelo Garcia Manzato, Rudinei Goularte

Proceedings of the Brazilian Symposium on Multimedia and the Web, 2012

A multimedia recommender system based on enriched user profiles.

Marcelo G. Manzato, Rudinei Goularte

Proceedings of the ACM Symposium on Applied Computing, 2012

Discovering latent factors from movies genres for enhanced recommendation.

Marcelo G. Manzato

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012

The participation of IntermidiaLab at the ImageCLEF 2012 Photo Annotation Task.

Marcelo G. Manzato

Proceedings of the CLEF 2012 Evaluation Labs and Workshop, 2012

2011

An architecture for content personalization based on peer-level annotations.

Marcelo Garcia Manzato

PhD thesis, 2011

An enhanced content selection mechanism for personalization of video news programmes.

Marcelo G. Manzato, Danilo Barbosa Coimbra, Rudinei Goularte

Multim. Syst., 2011

2010

Peersommender: A peer-level annotation based approach for multimedia recommendation.

Marcelo G. Manzato, Rudinei Goularte

J. Inf. Data Manag., 2010

2009

Evaluation of video news classification techniques for automatic content personalisation.

Marcelo G. Manzato, Alessandra A. Macedo, Rudinei Goularte

Int. J. Adv. Media Commun., 2009

Supporting multimedia recommender systems with peer-level annotations.

Marcelo G. Manzato, Rudinei Goularte

Proceedings of the XV Brazilian Symposium on Multimedia and the Web, 2009

Multimedia content personalization based on peer-level annotation.

Marcelo G. Manzato, Danilo Barbosa Coimbra, Rudinei Goularte

Proceedings of the 7th European Conference on Interactive TV and Video, 2009

2008

Interactive news documents for digital television.

Marcelo G. Manzato, Daniel Carnio Junqueira, Rudinei Goularte

Proceedings of the Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web, 2008

Video news classification for automatic content personalization: a genetic algorithm based approach.

Marcelo Garcia Manzato, Rudinei Goularte

Proceedings of the 14th Brazilian Symposium on Multimedia and Web Systems, 2008

2006

Live video adaptation: a context-aware approach.

Marcelo G. Manzato, Rudinei Goularte

Proceedings of the 11th Brazilian Symposium on Multimedia and the Web, 2006

Transcoding Evaluation in Live Video Adaptation.

Marcelo G. Manzato, Rudinei Goularte

Proceedings of the Fourth Latin American Web Congress (LA-Web 2006), 2006

2005

Devices Descriptions for Context-Based Content Adaptation.

Robson Eisinger, Marcelo G. Manzato, Rudinei Goularte

Proceedings of the Third Latin American Web Congress (LA-Web 2005), 1 October, 2005