Projekt NCN nr 06788



Prace opublikowane

  1. Szwabe, A., Misiorek, P., Walkowiak, P., Multi-Relational Learning for Recommendation of Matches between Semantic Structures, in: Grana, M., Toro, C., Howlett, R.J., Jain, L.C. (Eds.), Knowledge Engineering, Machine Learning and Lattice Computing with Applications, LNCS/LNAI Volume 7828, 2013, pp. 98-107 (link, pdf).

  2. Szwabe A., Misiorek P., Ciesielczyk M., Jedrzejek C., Collaborative Filtering Based on Bi-Relational Data Representation, Foundations of Computing and Decision Sciences. Volume 38, Issue 1, pp. 67–83, ISSN  0867-6356, DOI: 10.2478/v10209-011-0021-x, February 2013 (link, pdf).

  3. Szwabe A., Misiorek P., Ciesielczyk M., Representation of Propositional Data for Collaborative Filtering, in S. Omaru et al. (Eds.): Distributed Computing and Artificial Intelligence, Advances in Intelligent and Soft Computing (AIST), Volume 217, pp. 385-392, 2013, Springer International Publishing, ISBN 978-3-319-00550-8, DOI: 10.1007/978-3-319-00551-5_47 (link, pdf). 

  4. Styperek A., Ciesielczyk, M., Szwabe, A., SPARQL – Compliant Semantic Search Engine with an Intuitive User Interface, in: Nguyen, NT., Attachoo, B., Trawinski, B., Somboonviwat, K. (Eds.), Intelligent Information and Database System, LNCS, Volume 8397, 2014, pp. 201-210, Springer International Publishing, ISBN 978-3-319-05475-9, DOI 10.1007/978-3-319-05476-6_21 (link, pdf).

  5. Szwabe A., Misiorek P., Ciesielczyk M., Evaluating Bi-Relational Data Representation for Collaborative Filtering, International Journal of Artificial Intelligence, Volume 12, Issue 1, pp. 104–116, ISSN 0974-0635, March 2014 (link).

  6. Styperek A., Ciesielczyk M., Szwabe A., Semantic search engine with an intuitive user interface, in: Proceedings of the companion publication of the 23rd international conference on World wide web companion (WWW Companion '14). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 2014, pp. 383-384. DOI=10.1145/2567948.2577203 (link, pdf).

  7. Szwabe A., Misiorek P., Janasiewicz T., Walkowiak P., Holistic Entropy Reduction for Collaborative Filtering, Foundations of Computing and Decision Sciences. Volume 39, Issue 3, Pages 209–229, ISSN (Online) 2300-3405, DOI: 10.2478/fcds-2014-0012, September 2014 (link, pdf).

  8. Styperek A., Ciesielczyk M., Szwabe A., Misiorek P., "Evaluation of SPARQL-Compliant Semantic Search User Interfaces", Vietnam Journal of Computer Science, vol. 2, no. 3, Springer Berlin Heidelberg, pp. 191-199,  ISSN 2196-8888, DOI: 10.1007/s40595-015-0044-y, 2015 (link, pdf).

  9. Ciesielczyk M., Szwabe A., Morzy M, “On Efficient Link Recommendation in Social Networks Using Actor-Fact Matrices,” Scientific Programming, vol. 2015, Article ID 450215, 9 pages, 2015. doi:10.1155/2015/450215 (link, pdf).

  10. Szwabe A., Ciesielczyk M., Misiorek P, Blinkiewicz M., “Application of the tensor-based recommendation engine to semantic service matchmaking,” Proceedings of The Ninth International Conference on Advances in Semantic Processing, pp. 116-125, ISBN: 978-1-61208-420-6, July 2015, Nice, France (link, pdf).

  11. Szwabe A., Misiorek P., Ciesielczyk M., “Multilinear Filtering Based on a Hierarchical Structure of Covariance Matrices ,” Schedae Informaticae, vol. 24/2015, April 2016, pp. 103-112, DOI: 10.4467/20838476SI.15.010.3032 (link, pdf).

  12. Ciesielczyk, M., Szwabe, A., Morzy, M., and Misiorek, P., "Progressive Random Indexing: Dimensionality Reduction Preserving Local Network Dependencies." ACM Trans. Internet Technol. Volume 17, Issue 2, Article 20, pp. 20:1-20:21, DOI:, March 2017 (link, pdf).

  13. Szwabe A., Misiorek P., Ciesielczyk M. "Evaluation of Tensor-Based Algorithms for Real-Time Bidding Optimization." In: Nguyen N., Tojo S., Nguyen L., Trawiński B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science, vol 10191, pp. 160-169. Springer, Cham, DOI: 10.1007/978-3-319-54472-4_16, 2017 (link).

  14. Szwabe A., Misiorek P., Ciesielczyk M. "Tensor-Based Modeling of Temporal Features for Big Data CTR Estimation." In: Kozielski S., Mrozek D., Kasprowski P., Małysiak-Mrozek B., Kostrzewa D. (eds) Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation. BDAS 2017. Communications in Computer and Information Science, vol 716. pp. 16-27, Springer, Cham, DOI: 10.1007/978-3-319-58274-0_2, 2017 (link).

  15. Szwabe A., Misiorek P., Bąk J., Ciesielczyk M. "Tensor-Based Syntactic Feature Engineering for Ontology Instance Matching." In: Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L., Zurada J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science, vol 10246, pp. 609-622. Springer, Cham, DOI: 10.1007/978-3-319-59060-8_55, 2017 (link).

  16. Szwabe A., Misiorek P., Ciesielczyk M., "Logistic Regression Setup for RTB CTR Estimation", in: Proceedings of the 9th International Conference on Machine Learning and Computing, ICMLC 2017, Singapore, Singapore, pp. 61-70, ACM, New York, USA, DOI = 10.1145/3055635.3056584, 2017 (link, pdf).

  17. Ciesielczyk M., "Using Mutual Information for Feature Selection in Programmatic Advertising", in: Proceedings of the 2017 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA), pp. 290-295, IEEE, July 2017 (link).

  18. Szwabe A., "Kernel and Acquisition Function Setup for Bayesian Optimization of Gradient Boosting Hyperparameters", In: Nguyen N., Hoang, D. H., Hong, T-P, Pham, H., Trawiński, B.(eds), Intelligent Infor-mation and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science, vol 10751, pp. 297-306. Springer, Cham, DOI:, 2018 (link).

Prace przyjęte do publikacji

  1. Szwabe, A., Misiorek, P., Decision Trees as Interpretable Bank Credit Scoring Models, artykuł przyjęty na konferencję Beyond Databases, Architectures and Structures (BDAS 2018).

  2. Szwabe, A., Misiorek, P., Ciesielczyk, M., Bąk, J., Tensor-Based Ontology Data Processing for Semantic Service Matchmaking, artykuł przyjęty na konferencję Beyond Databases, Architectures and Structures (BDAS 2018).


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