CRACS Publicatons

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2014
Ricardo Queirós and José Paulo Leal and José Campos, "Sequencing Educational Resources with Seqins", in Computer Science and Information Systems, vol. 11, pp.1479–1497, October 2014.
João Santos and Ricardo Rocha, "A Team-Based Scheduling Model for Interfacing Or-Parallel Prolog Engines", in Computer Science and Information Systems, vol. 11, pp.1435–1454, October 2014.
Pedro Ribeiro and Fernando Silva, "G-Tries: a data structure for storing and finding subgraphs", in Data Mining and Knowledge Discovery, Springer US, vol. 28, pp.337–377, March 2014. Abstract  Download: j2014_DMKD_gtries.pdf (884.87 KB)
Sandra Alves and Maribel Fernández and Mário Florido and Ian Mackie, "Linearity: A Roadmap", in Journal of Logic and Computation, vol. 24, pp.513–529, June 2014.
Elena Bellodi and Evelina Lamma and Fabrizio Riguzzi and Vítor Santos Costa and Riccardo Zese, "Lifted Variable Elimination for Probabilistic Logic Programming", in Journal of Theory and Practice of Logic Programming (30th International Conference on Logic Programming (ICLP 2014) Special Issue), Cambridge University Press, vol. 14, pp.681–695, July 2014.
Flávio Cruz and Ricardo Rocha and Seth C. Goldstein and Frank Pfenning, "A Linear Logic Programming Language for Concurrent Programming over Graph Structures", in Journal of Theory and Practice of Logic Programming (30th International Conference on Logic Programming (ICLP 2014) Special Issue), Cambridge University Press, vol. 14, pp.493–507, July 2014.
Theofrastos Mantadelis and Ricardo Rocha and Paulo Moura, "Tabling, Rational Terms, and Coinduction Finally Together!", in Journal of Theory and Practice of Logic Programming (30th International Conference on Logic Programming (ICLP 2014) Special Issue), vol. 14, pp.429–443, July 2014.
Ricardo Queirós and Mário Pinto, "ESEIG Mobile: An M-Learning Approach in a Superior School", in International Journal of Knowledge-Based Organizations, IGI Global, vol. 4, pp.22–38, December 2014.
Peggy Peissig and Vítor Santos Costa and Michael Caldwell and Carla Rottscheit and Richard L. Berg et al., "Relational machine learning for electronic health record-driven phenotyping", in Journal of Biomedical Informatics, vol. 52, pp.260–270, December 2014.