Giuseppe Spillo

About Me

I am Giuseppe Spillo, Ph.D. Student at University of Bari, in the SWAP Research Group, supervised by Prof. Cataldo Musto and Prof. Marco de Gemmis.
My main research areas are Knowledge-aware Recommender Systems, Multi-Modal Recommender Systems, and Knowledge Representation.
Check-out my publications if you're interesed in my research!

Education

Ph.D. Student in Computer Science

October 2022 - current

University of Bari, SWAP Research Group
Research field: Knowledge-aware Recommender Systems based on Heterogenous Knowledge Sources
Supervisors: Prof. Cataldo Musto, Prof. Marco de Gemmis

Master Degree in Computer Science, curriculum Knowledge Engineering and Machine Intelligence

October 2019 - April 2022

University of Bari
Thesis: Neuro-symbolic Recommender Systems Combining Graph Neural Network and First-Order Logic Rules
Supervisors: Prof. Cataldo Musto, Prof. Giovanni Semeraro
Graduation mark: 110/110 cum Laude

Bachelor Degree in Computer Science, and Software Production Technologies

October 2016 - October 2019

University of Bari
Thesis: Generazione di Spiegazioni Contestuali per Recommender Systems mediante Modelli di Semantica Distribuzionale
Supervisor: Prof. Cataldo Musto
Graduation mark: 110/110 cum Laude

My publications

• Cataldo Musto, Giuseppe Spillo, Giovanni Semeraro (2023).
  Harnessing Distributional Semantics to Build Context-aware Justifications for Recommender Systems.
  User Modeling and User-Adapted Interaction

• Giuseppe Spillo (2023).
  Knowledge-Aware Recommender Systems based on Multi-Modal Information Sources.
  ACM RecSys 2023, Doctoral Consortium Paper

• Giuseppe Spillo, Allegra De Filippo, Cataldo Musto, Michela Milano, Giovanni Semeraro (2023).
  Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint.
  ACM RecSys 2023, Main Track Paper

• Giuseppe Spillo (2023).
  Combining Heterogeneous Embeddings for Knowledge-Aware Recommendation Models.
  ACM UMAP 2023, Doctoral Consortium Paper

• Giuseppe Spillo, Cataldo Musto, Marco Polignano, Pasquale Lops, Marco de de Gemmis, Giovanni Semearo (2023).
  Combining Graph Neural Networks and Sentence Encoders for Knowledge-aware Recommendations.
  ACM UMAP 2023, Main Track Paper
  Best Student Paper Award Winner

• Giuseppe Spillo, Cataldo Musto, Pasquale Lops, Marco de de Gemmis, Giovanni Semearo (2022).
  Exploiting Neuro-Symbolic Graph Embeddings based on First-Order Logical Rules for Knowledge-aware Recommendations.
  AIxIA 2022, Discussion Paper.

• Giuseppe Spillo, Cataldo Musto, Marco de de Gemmis, Pasquale Lops, Giovanni Semearo (2022).
  Knowledge-aware Recommendations Based on Neuro-Symbolic Graph Embeddings and First-Order Logical Rules.
  ACM RecSys 2022, Late-Breaking Results Paper.

• Giuseppe Spillo, Cataldo Musto, Marco de de Gemmis, Pasquale Lops, Giovanni Semearo (2020).
  Exploiting Distributional Semantics Models for Natural Language Context-aware Justifications for Recommender Systems.
  CLiC-it 2020

• Giuseppe Spillo, Cataldo Musto, Marco de de Gemmis, Pasquale Lops, Giovanni Semearo (2020).
  Exploiting Distributional Semantics Models for Natural Language Context-aware Justifications for Recommender Systems.
  IntRS Workshop, RecSys 2020