Pre-Processing Approaches Applied to Data Clustering Based Recommender Systems.

• Grant number: 16/04798-5
• Support Opportunities: Scholarships in Brazil - Master
• Start date: June 01, 2016
• End date: February 28, 2018
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Marcelo Garcia Manzato
• Grantee: Fernando Soares de Aguiar Neto
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Recommender systems have been widely applied in many areas, but the information available for the creation of such systems is poorly structured, given the lack of information provided by users. We propose approaches for pre-processing of the databases used in recommendations in order to elicit the most relevant information to the application. To this end, we explore categories present in databases, as well as relationships expressed by graphs. It is expected that such approaches reduce computational time as well as increase the quality of recommendations made by such algorithms.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DE AGUIAR NETO, FERNANDO S.; DA COSTA, ARTHUR F.; MANZATO, MARCELO G.; CAMPELLO, RICARDO J. G. B.. Pre-processing approaches for collaborative filtering based on hierarchical clustering. INFORMATION SCIENCES, v. 534, p. 172-191, SEP 2020. (16/04798-5, 13/07375-0, 16/20280-6)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

AGUIAR NETO, Fernando Soares de. Pre-processing approaches for collaborative filtering based on hierarchical clustering. 2018. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.