Banca de DEFESA: VICTOR MARTINEZ VIDAL PEREIRA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : VICTOR MARTINEZ VIDAL PEREIRA
DATE: 21/06/2022
TIME: 09:00
LOCAL: meet.google.com/rvg-upob-cth
TITLE:

Exploiting Linked Data in DBpedia to Reduce Prediction Error in Matrix Factorization Recommenders

KEY WORDS:

Recommender Systems, Matrix Factorization, Linked Open Data, Prediction Error

PAGES: 88
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Sistemas de Informação
SUMMARY:

Recommender Systems provide suggestions for items that are most likely of interest to users. Providing personalized recommendations is a challenge that can be addressed by filtering algorithms among which Collaborative Filtering (CF) has demonstrated much progress in the last few years. By using Matrix Factorization (MF) techniques, CF methods reduce prediction error by using optimization algorithms. However, they usually face problems such as data sparsity and prediction error. Studies point to the use of data available in Semantic Web as a path to improve recommender systems and address the challenges related to CF techniques. Motivated by these premises, the present work developed a data pipeline along with an algorithm that processes the Ratings Matrix combining semantic similarities of Linked Open Data (LOD) and estimates missing rat- ings. The experiments take subsets of three different datasets (Movielens, LastFM and LibraryThing), two semantic similarity metrics, Linked Data Similarity Distance (LDSD) and Resource Similarity (RESIM), and three MF-based algorithms (SVD, SVD++ and NMF). Our experiments reduced sparsity by more than 75% in Movielens subset and 28% in LastFM. Prediction error is reduced in all subsets with statistical confidence using parametric test one-way ANOVA followed by Tukey’s multiple comparison test.

BANKING MEMBERS:
Presidente - 2011187 - FREDERICO ARAUJO DURAO
Interno - 2357676 - DANILO BARBOSA COIMBRA
Externo ao Programa - 2973264 - RODRIGO ROCHA GOMES E SOUZA
Externo à Instituição - ADRIANO CÉSAR MACHADO PEREIRA - UFMG
Externa à Instituição - RAMON PEREIRA LOPES - UFRB