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NOMAD

NOMAD - Next-generation Open Mobile Apps Development


This project has been funded by the Autonomous Region of Sardinia, with grant PIA 2013 (total funding: EU 1.020.000).

Project Members

Università degli Studi di Cagliari - Dipartimento di Matematica e Informatica

Project Coordinators
  • Massimo Bartoletti
  • Salvatore Carta

Reseach Associates

  • Ludovico Boratto
  • Tiziana Cimoli
  • Paolo Pilloni
  • G. Michele Pinna
  • Roberto Saia

PhD Students

  • Nicola Atzei
  • Maurizio Murgia
  • Alessandro Sebastian Podda
  • Livio Pompianu

Temporary contract holders

  • Stefano Lande
  • Maria Luisa Mulas
  • Giordano Sini

Publications

2017

  • R. Saia, S. Carta. Evaluating Credit Card Transactions in the Frequency Domain for a Proactive Fraud Detection Approach. 14th International Conference on Security and Cryptography (SECRYPT), Madrid, Spain, 2017.
  • R. Saia, S. Carta. A Fourier Spectral Pattern Analysis to Design Credit Scoring Models. In Proc. International Conference on Internet of Things and Machine Learning (IML-2017), Liverpool city, United Kingdom, 2017.
  • R. Saia, S. Carta. A Frequency-domain-based Pattern Mining for Credit Card Fraud Detection. In Proc. 2nd International Conference on Internet of Things, Big Data and Security (IoTBDS-2017), Porto, Portugal, 2017.

2016

  • R. Saia, L. Boratto, S. Carta, G. Fenu.  Representing Items as Word-Embedding Vectors and Generating Recommendations by Measuring their Linear Independence. ACM Recommender Systems conference (RecSys-2016), Boston, MA, USA, 2016.
  • R. Saia, L. Boratto, S. Carta.  Improving the Accuracy of Latent-space-based Recommender Systems by Introducing a Cut-off Criterion. Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS), Brussels, Belgium, 2016.
  • N. Atzei, M. Bartoletti. Developing honest Java programs with Diogenes. To be presented at FORTE 2016.
  • R. Saia, L. Boratto, S. Carta, G. Fenu. Using Neural Word Embeddings to Model User Behavior and Detect User Segments. Accepted for publication in Knowledge-Based Systems (KBS), Elsevier, 2016.
  • R. Saia, L. Boratto, S. Carta, G. Fenu. Binary Sieves: Toward a Semantic Approach to User Segmentation for Behavioral Targeting. Accepted for publication in Future Generation Computer Systems (FGCS), Elsevier, 2016.
  • R. Saia, L. Boratto, S. Carta, G. Fenu. A semantic approach to remove incoherent items from a user profile and improve the accuracy of a recommender system. Accepted for publication in Journal of Intelligent Information Systems (JIIS), Springer, 2016.
  • R. Saia, L. Boratto, S. Carta, G. Fenu. Exploiting a Determinant-based Metric to Evaluate a Word-embeddings Matrix of Items.In Proc. IEEE International Conference on Data Mining series (ICDM), SERecSys Workshop, 2016.
  • R. Saia, L. Boratto, S. Carta, G. Fenu. Representing Items as Word-Embedding Vectors and Generating Recommendations by Measuring their Linear Independence. In Proc. ACM Recommender Systems conference (RecSys), 2016.
  • R. Saia, L. Boratto, S. Carta. Improving the Accuracy of Latent-space-based Recommender Systems by Introducing a Cut-off Criterion. In Proc. Workshop on Engineering Computer-Human Interaction in Recommender Systems (EnCHIReS), 2016.
  • R. Saia, S. Carta. A Linear-dependence-based Approach to Design Proactive Credit Scoring Models..In Proc. 8th International Conference on Knowledge Discovery and Information Retrieval (KDIR), 2016.
  • R. Saia, S. Carta. An Entropy Based Algorithm for Credit Scoring. Lecture Notes in Business Information Processing, Springer (LNBIP), 2016.