Publications

2021
[SNAM]: S. Antaris, D. Rafailidis, S. Girdzijauskas, “Knowledge Distillation on Neural Networks for Evolving Graphs”, Social Network Analysis and Mining, Springer, Vol.11, N.1, Article Number 100, 2021. [pdf]
[ASONAM’21]: S. Antaris, D. Rafailidis, S. Girdzijauskas, “Meta-reinforcement learning via buffering graph signatures for live video streaming events”. Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 385-392, The Hague, Netherlands, 2021. [pdf]
[BigData’21]: S. Antaris, D. Rafailidis, S. Girdzijauskas: “A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming”. Proceedings of the IEEE International Conference on Big Data, pp. 1787-1796, Orlando, FL, USA, 2021. [pdf]
[ECML/PKDD’21]: S. Antaris, D. Rafailidis, R. Arriaza, “Multi-Task Learning for User Engagement and Adoption in Live Video Streaming Events”. Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases,  Applied Data Science Track, pp. 463-478, Bilbao, Spain, 2021. [pdf]
[RecSys’21]: S. Antaris, D. Rafailidis, “Sequence Adaptation via Reinforcement Learning in Recommender Systems”. Proceedings of the 15th ACM Conference on Recommender Systems LBR, pp. 714-718, Amsterdam, Netherlands, 2021. [pdf]

2020
[TKDE]: M. Aliannejadi, D. Rafailidis, F. Crestani, “A Joint Two-Phase Time-Sensitive Regularized Collaborative Ranking Model for Point of Interest Recommendation”. IEEE Transactions on Knowledge and Data Engineering, Vol.32, N.6, pp. 1050-1063, 2020. [pdf]
[ASONAM’20]: S. Antaris, D. Rafailidis, “Distill2Vec: Dynamic Graph Representation Learning with Knowledge Distillation”. Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 60-64, The Hague, Netherlands, 2020. [pdf]
[ASONAM’20]: S. Antaris, D. Rafailidis, “VStreamDRLS: Dynamic Graph Representation Learning with Self-Attention for Enterprise Distributed Video Streaming Solutions”. Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 486-493, The Hague, Netherlands, 2020. [pdf]
[BigData’20]: S. Antaris, D. Rafailidis, S. Girdzijauskas: “EGAD: Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events”. Proceedings of the IEEE International Conference on Big Data, pp. 1455-1464, Atlanta, GA, USA, 2020. [pdf]

2019
[WI’19]: D. Rafailidis, “Bayesian Deep Learning with Trust and Distrust in Recommendation Systems”. Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, pp. 18-25, Thessaloniki, Greece, 2019, Best Paper Award. [pdf]
[ICTIR’19]: D. Rafailidis, F. Crestani, “Neural Attentive Cross-Domain Recommendation”. Proceedings of the5th ACM International Conference on the Theory of Information Retrieval, pp. 165-172, Santa Clara, CA, USA,  2019. [pdf]
[ECIR’19]: J. Manotumruksa, D. Rafailidis, C. Macdonald, I. Ounis, “On Cross-Domain Transfer in Venue Recommendation”. Proceedings of the 41st European Conference on Information Retrieval Research, pp. 443-456, Cologne, Germany, 2019. [pdf]
[WIMS’19]: D. Rafailidis, Y. Manolopoulos, “Can Virtual Assistants Produce Recommendations?”. Proceedings of the 9th ACM International Conference on Web Intelligence, Mining and Semantics, pp. 4:1-4:6, Seoul, Korea, 2019. [pdf]
[SIGIR’19]: D. Rafailidis, F. Crestani, “Adversarial Training for Review-Based Recommendations”. Proceedings of the 42nd ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1057-1060, Paris, France, 2019. [pdf]

2018
[TBD]: S. Antaris, D. Rafailidis, “In-memory Stream Indexing of Massive and Fast Incoming Multimedia Content“, IEEE Transactions on Big Data, Vol.4, N.1, pp. 40-54, 2018. [pdf]
[ESWA]: D. Rafailidis, “A Multi-Latent Transition model for evolving preferences in recommender systems“, Expert Systems with Applications, Elsevier, Vol. 104, pp. 97-106, 2018. [pdf]
[ECML/PKDD’18]: D. Rafailidis, F. Crestani, “GeoDCF: Deep Collaborative Filtering with Multifaceted Contextual Information in Location-based Social Networks”. Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 709-724, Dublin, Ireland, 2018. [pdf]
[ASONAM’18]: D. Rafailidis, F. Crestani, “Friend Recommendation in Location-Based Social Networks via Deep Pairwise Learning”. Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 421-428, Barcelona, Spain, 2018. [pdf]
[ICTIR’18]: M. Aliannejadi, D. Rafailidis, F. Crestani, “A Collaborative Ranking Model with Multiple Location-based Similarities for Venue Suggestion”. Proceedings of the4th ACM International Conference on the Theory of Information Retrieval, pp. 19-26, Tianjin, China, 2018. [pdf]

2017
[ESWA]: D. Rafailidis, P. Kefalas, Y. Manolopoulos, “Preference Dynamics with Multimodal User-Item Interactions in Social Media Recommendation“, Expert Systems with Applications, Elsevier, Vol. 74, pp. 11-18, 2017. [pdf]
[FGCS]: D. Rafailidis, E. Constantinou, Y. Manolopoulos, “Landmark Selection for Spectral Clustering based on Weighted PageRank“, Future Generation Computer Systems, Elsevier, Vol. 68, pp. 465-472, 2017. [pdf]
[CIKM’17]: D. Rafailidis, F. Crestani, “A Collaborative Ranking Model for Cross-Domain Recommendations”. Proceedings of the 26th ACM International Conference on International Conference on Information and Knowledge Management, pp. 2263-2266, Singapore, 2017. [pdf]
[ECML/PKDD’17]: D. Rafailidis, F. Crestani, “A Regularization Method with Inference of Trust and Distrust in Recommender Systems”. Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 253-268, Skopje, FYROM, 2017. [pdf]
[RecSys’17]: D. Rafailidis, F. Crestani, “Learning to Rank with Trust and Distrust in Recommender Systems”. Proceedings of the 11th ACM Conference on Recommender Systems, pp. 5 -13, Como, Italy, 2017. [pdf]
[ICTIR’17]: D. Rafailidis, F. Crestani, “Recommendation with Social Relationships via Deep Learning”. Proceedings of the 3rd ACM International Conference on the Theory of Information Retrieval, pp. 151-158, Amsterdam, Holland, 2017. [pdf]
[TPDL’17]: D. Rafailidis, F. Crestani, “Multiple Random Walks for Personalized Ranking with Trust and Distrust Relationships”. Proceedings of the 21st International Conference on Theory and Practice of Digital Libraries, pp. 473 – 484, Thessaloniki, Greece, 2017. [pdf]
[ECIR’17]: M. Aliannejadi, D. Rafailidis, F. Crestani, “Personalized Keyword Boosting for Venue Suggestion based on Multiple LBSNs”. Proceedings of the 39th European Conference on Information Retrieval Research, pp. 291-303, Aberdeen, Scotland UK, 2017. [pdf]

2016
[TCBB]: A. Axenopoulos, D. Rafailidis, G. Papadopoulos, E. Houstis, P. Daras, “Similarity Search of Flexible 3D Molecules Combining Local and Global Shape Descriptors“, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol.13, N.5, pp. 954-970, 2016. [pdf]
[SPL]: D. Rafailidis, “Supervised Hashing based on the Dimensions’ Value Cardinalities of Image Descriptors”, IEEE Signal Processing Letters, Vol.23, N.10, pp. 1479-1483, 2016. [pdf].
[TSMC]: D. Rafailidis, A. Nanopoulos, “Modeling Users Preference Dynamics and Side Information in Recommender Systems”, IEEE Transactions on Systems, Man and Cybernetics: Systems, Vol.46, N.6, pp. 782-792, 2016. [pdf]
[CIKM’16]: D. Rafailidis, F. Crestani, “Joint Collaborative Ranking with Social Relationships in Top-N Recommendation”. Proceedings of the 25th ACM International Conference on International Conference on Information and Knowledge Management, pp. 1393-1402, Indianapolis, IN, USA, 2016. [pdf]
[ASONAM’16]: D. Rafailidis, F. Crestani, “Network Completion via Joint Node Clustering and Similarity Learning”. Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 63-68, San Francisco, CA, USA, 2016. [pdf]
[ECML/PKDD’16]: D. Rafailidis, F. Crestani, “Top-N Recommendation via Joint Cross-Domain User Clustering and Similarity Learning”. Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, Part II, pp. 426-441, Riva del Garda, Italy, 2016. [pdf]
[SIGIR’16]: D. Rafailidis, F. Crestani, “Cluster-based Joint Matrix Factorization Hashing for Cross-Modal Retrieval”. Proceedings of the 39th ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 781-784, Pisa, Italy, 2016. [pdf]
[SIGIR’16]: D. Rafailidis, F. Crestani, “Collaborative Ranking with Social Relationships for Top-N Recommendations”. Proceedings of the 39th ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 785-788, Pisa, Italy, 2016. [pdf]
[SAC’16]: D. Rafailidis, “Clustering Nodes with Attributes via Graph Alignment”. Proceedings of the 31st ACM Symposium on Applied Computing, pp. 904-907, Pisa, Italy, 2016. [pdf]
[SAC’16]: D. Rafailidis, “Modeling Trust and Distrust Information in Recommender Systems via Joint Matrix Factorization with Signed Graphs”. Proceedings of the 31st ACM Symposium on Applied Computing, pp. 1060-1065, Pisa, Italy, 2016. [pdf]

2015
[IJMIR]: T. Semertzidis, D. Rafailidis, M. G. Strintzis, P. Daras, “The Influence of Image Descriptors′ Dimensions Value Cardinalities on Large-Scale Similarity Search”, International Journal of Multimedia Information Retrieval, Springer, Vol.4, N.3, pp. 187-204, 2015. [pdf]
[IPM]: T. Semertzidis, D. Rafailidis, M. G. Strintzis, P. Daras, “Large-Scale Spectral Clustering based on Pairwise Constraints”, Information Processing & Management,  Elsevier, Vol.51, N.5, pp. 616-624, 2015. [pdf]
[TOMCCAP]: S. Antaris, D. Rafailidis, “Similarity Search over the Cloud based on Image Descriptors′ Dimensions Value Cardinalities”, ACM Transactions on Multimedia Computing, Communications and Applications, Vol.11, N.4, Article Number 51, 2015. [pdf]
[BigData’15]: D. Rafailidis, S. Antaris, “Indexing Media Storms on Flink”. Proceedings of the IEEE International Conference on Big Data, pp. 2836-2838, Santa Clara, CA, USA, 2015. [pdf]
[MEDI’15]: E. Tiakas, D. Rafailidis, “Scalable Trajectory Similarity Search based on Locations in Spatial Networks”. Proceedings of the 5th International Conference on Model & Data Engineering, pp. 213-224, Island of Rhodes, Greece, 2015. [pdf]
[DEXA’15]: A. Papadopoulos, D. Rafailidis, G. Pallis, M.D. Dikaiakos, “Clustering Attributed Multi-graphs with Information Ranking”. Proceedings of the 26th International Conference on Database and Expert Systems Applications, pp. 432-446, Valencia, Spain, 2015. [pdf]
[ICMR’15]: D. Rafailidis, “Probabilistic Matrix Factorization with Semantic and Visual Neighborhoods for Image Tag Completion”. Proceedings of the 5th ACM International Conference on Multimedia Retrieval, pp. 527-530, Shanghai, China, 2015. [pdf]
[WWW’15]: D. Rafailidis, A. Nanopoulos, “Repeat Consumption Recommendation based on Users Preference Dynamics and Side Information”. Proceedings of the 24th ACM International Conference on World Wide Web, Companion Volume, pp. 99-100, Florence, Italy, 2015. [pdf]
[WWW’15]: D. Rafailidis, A. Nanopoulos, “Crossing the Boundaries of Communities via Limited Link Injection for Information Diffusion in Social Networks”. Proceedings of the 24th ACM International Conference on World Wide Web, Companion Volume, pp. 97-98, Florence, Italy, 2015. [pdf]
[SAC’15]: D. Rafailidis, Y. Manolopoulos, “Parallel Similarity Search based on the Dimensions Value Cardinalities of Image Descriptor Vectors”. Proceedings of the 30th ACM Symposium on Applied Computing, pp. 1023-1030, Salamanca, Spain, 2015. [pdf]

2014
[SNAM]: S. Antaris, D. Rafailidis, A. Nanopoulos, “Link Injection for Boosting Information Spread in Social Networks”, Social Network Analysis and Mining, Springer, Vol.4, N.1, Article Number 236, 2014. [pdf]
[JSS]: D. Rafailidis, A. Nanopoulos, E. Constantinou, “With a Little Help from New Friends: Boosting Information Cascades in Social Networks based on Link Injection”, Journal of Systems and Software, Elsevier, Vol.98, pp. 1-8, 2014. [pdf]
[TiiS]: D. Rafailidis, A. Axenopoulos, J. Etzold, S. Manolopoulou, P. Daras, “Content-based Tag Propagation and Tensor Factorization for Personalized Item Recommendation based on Social Tagging”, ACM Transactions on Interactive Intelligent Systems, Vol.3, N.4, Article Number 26, 2014. [pdf]
[RecSys’14]: D. Rafailidis, A. Nanopoulos, “Modeling the Dynamics of User Preferences in Coupled Tensor Factorization”. Proceedings of the 8th ACM Conference on Recommender Systems, pp. 321-324, Silicon Valley, CA, USA, 2014. [pdf]
[MEDI’14]: D. Rafailidis, E. Constantinou, Y. Manolopoulos, “Scalable Spectral Clustering with Weighted PageRank”. Proceedings of the 4th International Conference on Model & Data Engineering, pp. 289-300, Larnaca, Cyprus, 2014. [pdf]

2013
[PR]: D. Rafailidis, S. Manolopoulou, P. Daras, “A Unified Framework for Multimodal Retrieval”, Pattern Recognition, Elsevier, Vol.46, N.12, pp. 3358-3370, 2013. [pdf]
[TMM]: E. Tiakas, D. Rafailidis, A. Dimou, P. Daras, “MSIDX: Multi-Sort Indexing for Efficient Content-based Image Search and Retrieval”, IEEE Transactions on Multimedia, Vol.15, N.6, pp. 1415-1430, 2013. [pdf]
[TSMC]: D. Rafailidis, P. Daras, “The TFC Model: Tensor Factorization and Tag Clustering for Item Recommendation in Social Tagging Systems”, IEEE Transactions on Systems, Man and Cybernetics: Systems, Vol.43, N.3, pp. 673-688, 2013. [pdf]
[SPIC]: M. Lazaridis, A. Axenopoulos, D. Rafailidis, P. Daras, “Multimedia Search and Retrieval using Multimodal Annotation Propagation and Indexing Techniques”, Signal Processing: Image Communication, Special Issue on Image Search and Augmented Reality, Elsevier, Vol.28, N.4, pp. 351-367, 2013. [pdf]
[MediaEval’13]: D. Rafailidis, T. Semertzidis, M. Lazaridis, M. G. Strintzis, P. Daras, “A Data-Driven Approach for Social Event Detection”. Proceedings of MediaEval’13, CEUR-WS.org/-Vol.1043, Barcelona, Spain, 2013. [pdf]
[WI’13]: A. Nanopoulos, D. Rafailidis, Y. Karydis, “Matrix Factorization with Content Relationships for Media Personalization”. Proceedings of the 11th Conference on Wirtschaftsinformatik, pp. 87-101, Leipzig, Germany, 2013. [pdf]
[SMR]: T. Semertzidis, D. Rafailidis, E. Tiakas, M. G. Strintzis, P. Daras, “Multimedia Indexing, Search and Retrieval in Large Databases of Social Networks”, in N. Ramzan et al. (eds) Social Media Retrieval, Computer Communications and Networks series, Springer-Verlag, pp. 43-63, 2013, ISBN 978-1-4471-4554-7. [pdf]

2011
[MTAP]: D. Rafailidis, A. Nanopoulos, Y. Manolopoulos, “Nonlinear Dimensionality Reduction for Efficient and Effective Audio Similarity Searching”, Multimedia Tools and Applications, Springer, Vol.51, N.3, pp. 881-895, 2011. [pdf]

2010
[TASLP]: A. Nanopoulos, D. Rafailidis, P. Symeonidis, Y. Manolopoulos, “MusicBox: Personalized Music Recommendation based on Cubic Analysis of Social Tags”, IEEE Transactions on Audio, Speech and Language Processing, Vol.18, N.2, pp. 407-412, 2010. [pdf]
[IJMDEM]: D. Rafailidis, A. Nanopoulos, Y. Manolopoulos, “Building Tag-Aware groups for Music High- Order Ranking and Topic Discovery”, International Journal of Multimedia Data Engineering and Management, IGI-Global, Vol. 1, N. 3, pp. 1-18, 2010. [pdf]

2009
[IPM]: A. Nanopoulos, D. Rafailidis, M. Ruxanda, Y. Manolopoulos, “Music Search Engines: Specifications and Challenges”, Information Processing & Management, Elsevier, Vol.45, N.3, pp. 392-396, 2009. [pdf]

2008
[ISMIR’08]: D. Rafailidis, A. Nanopoulos, E. Cambouropoulos, Y. Manolopoulos, “Detection of Stream Segments in Symbolic Musical Data”. Proceedings of the 9th International Symposium on Music Information Retrieval, pp. 83-88, Philadelphia, PA, USA, 2008. [pdf]