Researcher

Spanakis, Gerasimos

Assistant Professor, Researcher

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  1. 2018
  2. Published
    Mino, A., & Spanakis, G. (2018). LoGAN: Generating Logos with a Generative Adversarial Neural Network Conditioned on Color. In 17th IEEE International Conference on Machine Learning and Applications, ICMLA 2018, Orlando, FL, USA, December 17-20, 2018 (pp. 965-970) https://doi.org/10.1109/ICMLA.2018.00157
  3. Published
    Moers, T., Krebs, F., & Spanakis, G. (2018). SEMTec: Social Emotion Mining Techniques for Analysis and Prediction of Facebook Post Reactions. In J. van den Herik, & A. P. Rocha (Eds.), Agents and Artificial Intelligence (pp. 361-382). Cham: Springer International Publishing AG.
  4. Published
    Velasquez Sosa, J., & Spanakis, G. (2018). Neural Attention and Morphological Word Embedding for Contract Element Extraction. Poster session presented at 30th Benelux Conference on Artificial Intelligence
    , Den Bosch, Netherlands.
  5. Published
    Woszczyk, D., & Spanakis, G. (2018). MaaSim: A Liveability Simulation for Improving the Quality of Life in Cities. In C. Alzate, A. Monreale, H. Assem, A. Bifet, T. S. Buda, B. Caglayan, B. Drury, E. García-Martín, R. Gavaldà, S. Kramer, N. Lavesson, M. Madden, I. Molloy, M-I. Nicolae, ... M. Sinn (Eds.), ECML PKDD 2018 Workshops (pp. 118-133). Cham: Springer International Publishing AG.
  6. Published
    Krebs, F., Lubascher, B., Moers, T., Schaap, P., & Spanakis, G. (2018). Social Emotion Mining Techniques for Facebook Posts Reaction Prediction. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence (pp. 211-220) https://doi.org/10.5220/0006656002110220
  7. 2017
  8. Published
    Bartl, A., & Spanakis, G. (2017). A Retrieval-Based Dialogue System Utilizing Utterance and Context Embeddings. In 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 1120-1125). IEEE. https://doi.org/10.1109/ICMLA.2017.00011
  9. Published
    Hermans, J. R., Spanakis, G., & Möckel, R. (2017). Accumulated Gradient Normalization. In M-L. Zhang, & Y-K. Noh (Eds.), Proceedings of the 9th Asian Conference on Machine Learning (Vol. 77, pp. 439-454). (Proceedings of Machine Learning Research). Proceedings of Machine Learning Research.
  10. Published
    Hagedoorn, T. R., & Spanakis, G. (2017). Massive Open Online Courses Temporal Profiling for Dropout Prediction. In 29th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2017, Boston, MA, USA, November 6-8, 2017 (pp. 231-238)
  11. Published
    Prabhakar, S., Spanakis, G., & Zaiane, O. (2017). Reciprocal Recommender System for Learners in Massive Open Online Courses (MOOCs). In International Conference on Web-Based Learning (ICWL) (pp. 157-167). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-66733-1_17
  12. Published
  13. Published
    Vrancken, T., Tenbrock, D., Reick, S., Bozhinovski, D., Weiss, G., & Spanakis, G. (2017). Multi-Agent Parking Place Simulation. In Y. Demazeau, P. Davidsson, J. Bajo, & Z. Vale (Eds.), Advances in Practical Applications of Cyber-Physical Multi-Agent Systems: The PAAMS Collection: 15th International Conference, PAAMS 2017, Porto, Portugal, June 21-23, 2017, Proceedings (pp. 272-283). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-59930-4_22
  14. Published
    Price, S., Hall, W., Earl, G., Tiropanis, T., Tinati, R., Wang, X., ... Wessels, B. (2017). Worldwide Universities Network (WUN) Web Observatory: Applying Lessons from the Web to Transform the Research Data Ecosystem. In International World Wide Web Conference: (WOW'17) Web Observatory Workshop 2017 (pp. 1665-1667) https://doi.org/10.1145/3041021.3051691
  15. Published
    Bakhshinategh, B., Spanakis, G., Zaiane, O., & ElAtia, S. (2017). A Course Recommender System based on Graduating Attributes. In Proceedings of the 9th International Conference on Computer Supported Education - Volume 1: CSEDU (pp. 347-354) https://doi.org/10.5220/0006318803470354
  16. Published
    Spanakis, G., & Weiss, G. (2017). Enhancing Visual Clustering Using Adaptive Moving Self-Organizing Maps (AMSOM). In Agents and Artificial Intelligence (pp. 189-211). (Lecture Notes in Computer Science; Vol. 10162). https://doi.org/10.1007/978-3-319-53354-4_11
  17. 2016
  18. Published
  19. Published
    Spanakis, G., Weiss, G., & Roefs, A. (2016). Enhancing Classification of Ecological Momentary Assessment Data Using Bagging and Boosting. In IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI 2016) (pp. 388-395). IEEE. https://doi.org/10.1109/ICTAI.2016.0066
  20. Published
    Bruggermann, D., Hermey, Y., Orth, C., Schneider, D., Selzer, S., & Spanakis, G. (2016). Storyline detection and tracking using Dynamic Latent Dirichlet Allocation. In Proceedings of the 2nd Workshop on Computing News Storylines (CNS 2016), EMNLP 2016 (pp. 9-19). Association for Computational Linguistics.
  21. Published
    Brüggermann, D., Hermey, Y., Orth, C., Schneider, D., Selzer, S., & Spanakis, G. (2016). Towards a Topic Discovery and Tracking System with Application to News Items. In J. F. Quesada, F-J. Martín Mateos, & T. López Soto (Eds.), Future and Emerging Trends in Language Technology: Machine Learning and Big Data: Second International Workshop, FETLT 2016, Seville, Spain, November 30 --December 2, 2016, Revised Selected Papers (pp. 183-197). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-69365-1_15
  22. Published
  23. Published
  24. Published
    Spanakis, G., Weiss, G., & Roefs, A. (2016). Bagged Boosted Trees for Classification of Ecological Momentary Assessment Data. In ECAI 2016 - 22nd European Conference on Artificial Intelligence, 29 August-2 September 2016, The Hague, The Netherlands - Including Prestigious Applications of Artificial Intelligence (PAIS 2016) (pp. 1612-1613) https://doi.org/10.3233/978-1-61499-672-9-1612
  25. Published
  26. 2015
  27. Published
    Wittlinger, C., Spanakis, G., & Weiss, G. (2015). Flexible Deep Neural Network structure with application to Natural Language Processing. In BNAIC 2015 THE 27TH BENELUX CONFERENCE ON ARTIFICIAL INTELLIGENCE (Vol. 1)
  28. Published
  29. Published
    Spanakis, G., Weiss, G., Boh, B., & Roefs, A. (2015). Network Analysis of Ecological Momentary Assessment Data for Monitoring and Understanding Eating Behavior. In X. Zheng, D. D. Zeng, H. Chen, & J. S. Leischow (Eds.), Smart Health: International Conference, ICSH 2015, Phoenix, AZ, USA, November 17-18, 2015. Revised Selected Papers (pp. 43-54). Cham: Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-29175-8_5