Experimental Guidelines for Semantic-Based Regularization

  • Claudio SaccàEmail author
  • Michelangelo Diligenti
  • Marco Gori
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 26)


This paper presents a novel approach for learning with constraints called Semantic-Based Regularization. This paper shows how prior knowledge in form of First Order Logic (FOL) clauses, converted into a set of continuous constraints and integrated into a learning framework, allows to jointly learn from examples and semantic knowledge. A series of experiments on artificial learning tasks and application of text categorization in relational context will be presented to emphasize the benefits given by the introduction of logic rules into the learning process.


Text Categorization First Order Logic Logic Rule Logic Knowledge Kernel Machine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Chapelle, O.: Training a support vector machine in the primal. Neural Computation 19(5), 1155–1178 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Diligenti, M., Gori, M., Maggini, M., Rigutini, L.: Bridging logic and kernel machines. Machine Learning, 1–32 (2011)Google Scholar
  3. 3.
    Frasconi, P., Passerini, A.: Learning with kernels and logical representations. In: De Raedt, L., Frasconi, P., Kersting, K., Muggleton, S.H. (eds.) Probabilistic ILP 2007. LNCS (LNAI), vol. 4911, pp. 56–91. Springer, Heidelberg (2008)Google Scholar
  4. 4.
    Richardson, M., Domingos, P.: Markov logic networks. Machine Learning 62(1-2), 107–136 (2006)CrossRefGoogle Scholar
  5. 5.
    Saccà, C., Diligenti, M., Maggini, M., Gori, M.: Integrating logic knowledge into graph regularization: an application to image tagging. In: Ninth Workshop on Mining and Learning with Graphs - MLG (KDD) (2011)Google Scholar
  6. 6.
    Saccà, C., Diligenti, M., Maggini, M., Gori, M.: Learning to tag from logic constraints in hyperlinked environments. In: ICMLA, pp. 251–256 (2011)Google Scholar
  7. 7.
    Saccà, C., Frandina, S., Diligenti, M., Gori, M.: Constrained-based learning for text categorization. In: Workshop on COmbining COnstraint solving with MIning and LEarning - CoCoMiLe (ECAI) (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Claudio Saccà
    • 1
    Email author
  • Michelangelo Diligenti
    • 1
  • Marco Gori
    • 1
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversità di SienaSienaItaly

Personalised recommendations