Publications

Link to my Google Scholar Profile.

International Books/Monographs

  1. P. Symeonidis, A. Zioupos: “Matrix and Tensor Factorization Techniques for Recommender Systems”, Series: Springer Briefs in Computer Science, 2017, 102 pages, 29 b/w illustrations, 22 illustrations in colour, ISBN,978-3-319-41356-3 (DOI)
  2. P. Symeonidis, D. Ntempos, Y. Manolopoulos: “Recommender Systems for Location-based Social Networks”, Series: Springer Briefs in Electrical and Computer Engineering, 2014, 118 pages, 41 illus., Softcover, ISBN 978-1-4939-0285-9 (DOI)
  3. L. Balby Marinho, A. Hotho, R. Jäschke, A. Nanopoulos, S. Rendle, L. Schmidt-Thieme, G. Stumme, P. Symeonidis: “Recommender Systems for Social Tagging Systems”, Series: SpringerBriefs in Electrical and Computer Engineering, 2012, 115 pages, 35 illus., Softcover, ISBN 978-1-4614-1893-1 (DOI)

Greek Textbooks

  1. Παναγιώτης Συμεωνίδης, (2023). Ευφυή Συστήματα Συστάσεων. Αθήνα, Κάλλιπος, Ανοικτές Ακαδημαϊκές Εκδόσεις. http://dx.doi.org/10.57713/kallipos-156 ISBN: 978-618-5726-37-9
  2. Παναγιώτης Συμεωνίδης, Γούναρης Αναστάσιος, “Βάσεις Αποθήκες και Εξόρυξη Δεδομένων: Στο Εργαστήριο με τον SQL Server”, Αθήνα: Σύνδεσμος Ελληνικών Ακαδημαϊκών Βιβλιοθηκών. ISBN: 978-960-603-021-5 (DOI)

Journal Publications

  1. Symeonidis, P., Chaltsev, D., Berbague, C. and Zanker, M., 2022. Sequence-aware news recommendations by combining intra-with inter-session user information. Information Retrieval Journal, 25(4), pp.461-480.
  2. Symeonidis, P., Chairistanidis, S. & Zanker, M. Safe, effective and explainable drug recommendation based on medical data integration. User Modelling and User-adapted Interaction (2022). https://doi.org/10.1007/s11257-022-09342-x
  3. Berbague, C.E., Seridi-Bouchelaghem, H., El-Islem, K.N., Symeonidis, P. and Zanker, M., 2022. An evolutionary-based approach for providing accurate and novel recommendations. International Journal of Business Intelligence and Data Mining, 21(2), pp.129-148.
  4. Zheng, Y., Chen, L., Zanker, M., Symeonidis, P.: JIIS preface for the special issue on advances in recommender systems. Journal of Intelligent Information Systems (Springer) 58(2): 223-225 (2022)
  5. Symeonidis, P., Kirjackaja, L., Zanker, M. “Session-based News Recommendations using SimRank on multi-modal Graphs”, Expert Systems with Applications (Elsevier), 2021  https://doi.org/10.1016/j.eswa.2021.115028
  6. Berbague, C., Karabadji, N., Seridi, H., Symeonidis, P., Manolopoulos, Y., Dhifli, W. “An overlapping clustering approach for precision, and novelty-aware recommendation”, Expert Systems with Applications (Elsevier) vol. 177, 2021
  7. Makbule Gulcin Ozsoy, Diarmuid O’Reilly-Morgan, Panagiotis Symeonidis, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor: MP4Rec: Explainable and Accurate Top-N Recommendations in Heterogeneous Information Networks. IEEE Access (8) pages: 181835-181847 (2020)
  8. Symeonidis, P., Kirjackaja, L., Zanker, M. “Session‑aware news recommendations using random walks on time‑evolving heterogeneous information networks”, User Modelling and User-Adapted Interaction, https://doi.org/10.1007/s11257-020-09261-9, 2020
  9. P. Symeonidis, L. Coba, M. Zanker: “Personalized Novel and Explainable Matrix Factorization”, Data and Knowledge Engineering Journal, Elsevier (accepted for publication in June 2019)
  10. P. Symeonidis, L. Coba, M. Zanker: “Counteracting the Filter Bubble in Recommender Systems: Novelty-aware Matrix Factorization, Intelligenza Artificiale, IOS Press (accepted for publication in June 2019)
  11. P. Kefalas, P. Symeonidis, Y. Manolopoulos: “Recommendations based on a Heterogeneous Spatio-temporal Social Network”, World Wide Web, Vol. 21,N. 2, pp. 345-371, 2017. (Impact factor in 2017: 1.405)
  12. P. Symeonidis, D. Malakoiudis: “Multi-Modal Matrix Factorization with Side Information for Recommending Massive Open Online Courses”, Expert Systems with Applications, Vol. 118, pp. 261 – 271, 2019, DOI:https://doi.org/10.1016/j.eswa.2018.09.053
  13. P. Kefalas, P. Symeonidis, Y. Manolopoulos: “A Graph-based Taxonomy of Recommendation Algorithms and Systems in LBSNs”, IEEE Transactions on Knowledge & Data Engineering, Vol.28, N.3, pp. 604-622, 2016. (Impact factor in 2016: 3.438)
  14. P. Symeonidis: “ClustHOSVD: Item Recommendation by Combining Semantically-enhanced Tag Clustering with Tensor HOSVD”, IEEE Transactions on Systems, Man & Cybernetics – Part A: Systems &Humans, Vol. 46, No. 9, 2016. (Impact factor in 2016: 2.350)
  15. M. Sattari, I. Toroslu, P. Karagoz, P. Symeonidis, Y. Manolopoulos: “Extended Feature Combination Model forRecommendations in Location-based Mobile Services”, Knowledge & Information Systems, Vol.3, N.44, pp. 629-661,2015. (Impact factor in 2015: 1.702)
  16. Z.F. Siddiqui, E. Tiakas, P. Symeonidis, M. Spiliopoulou, Y. Manolopoulos: “Learning Relational User Profiles and Recommending Items as their Preferences Change”, International Journal of AI Tools, Vol.24, N.2, 2015 (impact factor in 2015: 0.530)
  17. P. Symeonidis, E. Tiakas: “Transitive Node Similarity: Predicting and Recommending Links in Signed Social Networks”, World Wide Web, Vol.17, No.4, pp.743-776, 2014. (impact factor in 2014: 1.474)
  18. P. Symeonidis, E. Tiakas, Y. Manolopoulos: “A Unified Framework for Link and Rating Prediction in Multi-modal SocialNetworks”, International Journal ofSocial Network Mining, Vol.1, No.3/4, 2013.
  19. P. Symeonidis, N. Mantas: “Spectral Clustering for Link Prediction in Social Networks with Positive and Negative Links”, Social Network Analysis & Mining, Vol.3, No.4, pp.1433-1447, 2013. (impact factor in 2013: 0.503)
  20. P.Symeonidis, N. Iakovidou, N. Mantas, Y. Manolopoulos: “From Biological to Social Networks: Link prediction based on Multi-way Spectral Clustering”, Data & Knowledge Engineering, Vol.87, pp.226-242, 2013. (impact factor in 2013: 1.489)
  21. P. Longinidis, P. Symeonidis: “Corporate Dividend Policy Determinants: Intelligent versus a Traditional Approach”, Intelligent Systems in Accounting, Finance & Management, Vol.20, No.2, pp.111-139, 2013.
  22. A. Papadimitriou, P. Symeonidis, Y. Manolopoulos: “Fast and Accurate Link Prediction in Social Networking Systems”, Journal of Systems & Software, Vol.85, No.9, pp.2119-2132, 2012. (impact factor in 2012: 1.135)
  23. A. Papadimitriou, P. Symeonidis, Y. Manolopoulos: “A Generalized Taxonomy of Explanations Styles for Traditional and Social Recommender Systems”, Data Mining & Knowledge Discovery, pp.1-29, 2011. (impact factor in 2011:1.545)
  24. P. Symeonidis, A. Nanopoulos, Y. Manolopoulos: “A Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis”, IEEE Transactions on Knowledge & Data Engineering, Vol.22, No.2, 2010. (impact factor in 2010: 1.851)
  25. A.Nanopoulos, D. Rafailidis, P. Symeonidis, Y. Manolopoulos: “MusicBox: Personalized Music Recommendation based on Cubic Analysis of Social Tags”, IEEE Transactions on Audio, Speech &Language Processing, Vol.18, No.2, 2010. (impact factor in 2010: 1.668)
  26. A. Deligiaouri, P. Symeonidis: “Skai (TV) – YouTube Debate”: A New Era of Internetized Television Politics”, International Journal of E-Politics, Vol.1, No.2, 2010 (publisher: IGI global).
  27. P. Symeonidis, A. Deligiaouri: “Recommending Posts in Political Blogs based on Tensor Dimensionality Reduction”, International Journal of Engineering Intelligent Systems, Vol.17, No.2-3, 2009. (impact factor in 2009: 0.205)
  28. P. Symeonidis, A. Nanopoulos, Y. Manolopoulos: “Providing Justifications in Recommender Systems”, IEEE Transactions on Systems, Man & Cybernetics – Part A: Systems & Humans, Vol.38, No.6, 2008. (impactfactor in 2008: 1.350)
  29. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Nearest-biclusters Collaborative Filtering with Constant and Coherent Values”, Information Retrieval, Vol.11, No.1, 2008. (5-year impact factor in 2008: 1.396)
  30. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Collaborative Filtering Systems: Combining Effectiveness and Efficiency”, Expert Systems with Applications, Vol.34, No.4, pp.51-75, 2008. (impact factor in 2008: 2.596)

Book Chapters

  1. G. Sottocornola, F. Stella, P. Symeonidis, M. Zanker, I. Krajger, R. Faullant, and E. Schwarz: Identifying Innovative Idea Proposals with Topic Models—A Case Study from SPA Tourism. In: Sigala M., Rahimi R., Thelwall M. (eds) Big Data and Innovation in Tourism, Travel, and Hospitality. Springer, Singapore, pp 115-133, 2019
  2. P. Symeonidis, D. Malakoudis: “MoocRec.com: Massive Open Online Courses recommender system” chapter in the book entitled “Collaborative Recommendations: Algorithms, Practical Challenges and Applications” (to appear in the end of 2018).
  3. P. Symeonidis: “Matrix and Tensor Factorization in Recommender Systems”, chapter in the book entitled “Graph-based Social Media Analysis”, by I. Pitas (ed.), CRC Press, Taylor & Francis group, Chapman & Hall/CRC, pp. 187-210, 2015, 2015.
  4. L. Marinho, A. Nanopoulos, L. Schmidt-Thieme, R. Jaschke, A. Hotho, G.Stumme, P. Symeonidis: “Social Tagging Recommender Systems”, chapter in book entitled “Recommender Systems Handbook”, by F. Ricci, L. Rokach, B. Shaphira, P.B. Kantor (eds.): LNCS Springer Book, pp. 615-644, 2011.
  5. A. Deligiaouri, P. Symeonidis: “Internetized Television Debates: Enhancing Citizens’ Participation”, chapter in book entitled “E-Politics and Organizational Implications of the Internet: Power, Influence and Social Change” by C.R. Livermore (ed.), IGI Global, 2011.
  6. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Nearest-biclusters Collaborative Filtering based on constant values”, chapter in book entitled “Advances in Web Mining and Web Usage Analysis”, by O. Nasraoui, O. Zaiane, M. Spiliopoulou, M.Mobasher, B. Masand, P. Yu (eds.), LNCS Springer, Vol.4811, pp.36-55, 2007.

Conference Papers

  1. Symeonidis, P., Chairistanidis, S., & Zanker, M. (2022, November). Deep Reinforcement Learning for Medicine Recommendation. In 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 85-90). IEEE.
  2. Symeonidis, P., Kostoulas, T., Danilatou, V., Andras, C., & Chairistanidis, S. (2022, November). Mortality Prediction and Safe Drug Recommendation for Critically-ill Patients. In 2022 IEEE 22nd International Conference on Bioinformatics and Bioengineering (BIBE) (pp. 79-84). IEEE.
  3. Symeonidis, P., Kirjackaja, L., Zanker, M. “Session-based Recommendation along with the Session Style of Explanation”, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 147-162, Grenoble France, 2022
  4. Panagiotis Symeonidis, Stergios Chairistanidis, Markus Zanker: Recommending What Drug to Prescribe Next for Accurate and Explainable Medical Decisions. IEEE Computer-based Medical Systems (IEEE CBMS 2021): 213-218
  5. Panagiotis Symeonidis, Christos Andras, Markus Zanker: Treatment Recommendations for COVID-19 Patients along with Robust Explanations. IEEE Computer-based Medical Systems (IEEE CBMS 2021) 2021: 207-212
  6. Panagiotis Symeonidis, Dmitry Chaltsev, Markus Zanker, Yannis Manolopoulos: News Recommendations by Combining Intra-session with Inter-session and Content-Based Probabilistic Modelling. International Conference on Computational Collective Intelligence (ICCCI 2021): 154-166
  7. Panagiotis Symeonidis: Similarity Search, Recommendation and Explainability over Graphs in Different Domains: Social Media, News, and Health Industry. IEEE International Conference on Web Engineering (IEEE ICWE 2021): 537-541, 2020
  8. Panagiotis Symeonidis, Andrea Janes, Dmitry Chaltsev, Philip Giuliani, Daniel Morandini, Andreas Unterhuber, Ludovik Coba, Markus Zanker: Recommending the Video to Watch Next: An Offline and Online Evaluation at YOUTV.de. ACM Recommender Systems Conference (RecSys 2020): 299-308
  9. L. Coba, M. Zanker, L. Rook, P. Symeonidis: “Decision Making Strategies Differ in the Presence of Collaborative Explanations: Two Conjoint Studies” Proceedings of the 24thInternational Conference on Intelligent User Interfaces, (to appear), Los Angeles, 2019.
  10. G. Sottocornola, P. Symeonidis, M. Zanker: “Session-based News Recommendations”, Companion Proceedings of  The Web Conference 2018, pp. 1395-1399, 2018.
    International World Wide Web Conferences Steering Committee.
  11. L. Çoba, P.Symeonidis, M. Zanker: “Replicating and Improving Top-N Recommendations in Open Source Packages”, Proceedings of the 8th International Conference on Web Intelligence, Mining and Semantics (WIMS), Novi Sad, Serbia, 2018.
  12. L. Coba, M. Zanker, L.Rook, P. Symeonidis: “Exploring Users’ Perception of Rating Summary Statistics”, Proceedings of the 26th Conferenceon User Modeling, Adaptation and Personalization (UMAP), 2018.
  13. L. Çoba, P. Symeonidis, M. Zanker: “Reproducing and Prototyping Recommender Systems in R”, Proceedings of the 8th Italian Information Retrieval Workshop, 2017
  14. L. Çoba, P.Symeonidis, M. Zanker: “Visual Analysis of Recommendation Performance”, Proceedings of the 11th ACM Conference on Recommender Systems (RecSys), pp.362-363, 2017.
  15. P. Symeonidis, S. Chairistanidis: “CheckInShop.eu: A Sensor-based Recommender System for micro-location Marketing”, Proceedings ofthe 11th ACM Conference on Recommender Systems (RecSys), pp.351-352,2017
  16. P. Symeonidis: “Matrix and Tensor Decomposition in Recommender Systems”, Tutorial Presentation at ACM RecSys’2016 conference, September 2016, Boston, MA.
  17. P. Kefalas, P.Symeonidis: “Recommending Friends and Locations over a Heterogeneous Spatio-temporal Graph”, Proceedings of the 5thInternational Conference on Model & Data Engineering (MEDI), pp.271-284, Island of Rhodes, Greece, 2015.
  18. P. Symeonidis, C. Perentis: “Link Prediction in Multi-modal Social Networks”, Proceedings of the International Conference on Machine Learning & Knowledge Discovery in Databases (ECML/PKDD), pp. 147-162, Nancy France, 2014
  19. Z.F. Siddiqui, E.Tiakas, P. Symeonidis, M. Spiliopoulou, Y. Manolopoulos: “xStreams: Providing Item Recommendations to Users with Time-evolving Preferences”, Proceedings of the 4thInternational Conference on Web Intelligence, Mining & Semantics (WIMS),Thessaloniki, Greece, 2014.
  20. P. Kefalas, P. Symeonidis, Y. Manolopoulos: “New Perspectives for Recommendations in Location-based Social Networks: Time, Privacy and Explainability”, Proceedings of the 5thInternational Conference on Management of Emergent Digital EcoSystems (MEDES), pp.1-8, Neumuenster Abbey, Luxembourg, 2013.
  21. P. Symeonidis, A.Krinis, Y. Manolopoulos: “GeoSocialRec: Explaining Recommendations in Location-based Social Networks”, Proceedings of the 17th East-European Conference on Advanced Databases & Information Systems (ADBIS), pp. 84-97, Genova, Italy, 2013.
  22. P. Symeonidis., I.Kehayov, Y. Manolopoulos: “Text Classification by Aggregation of SVD Eigenvectors”, Proceedings of the 16thEast-European Conference on Advances in Databases & Information Systems(ADBIS), pp.385-398, Poznan, Poland, 2012.
  23. M. Sattari, I.Toroslu, P. Senkul, M. Manguoglu, P. Symeonidis, Y. Manolopoulos: “Geo-activityRecommendations by using Improved Feature Combination”, Proceedings of the 4th ACM UNICOMP International Workshop onLocation-Based Social Networks (LBSN), Pittsburgh, PA, 2012.
  24. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: “Scalable Link Prediction in Social Networks based on Local Graph Characteristics”, Proceedings of the 9th International Conference on Information Technology: NewGenerations (ITNG), Las Vegas, NV, 2012
  25. P. Symeonidis, E.Tiakas, Y. Manolopoulos: “Product Recommendation and Rating Prediction based onMulti-modal Social Networks”, Proceedings of the 5th ACM Conference in Recommender Systems (RecSys), Chicago,IL, 2011.
  26. P. Symeonidis, A.Papadimitriou, Y. Manolopoulos, P. Senkul, I. Toroslu: “Geo-social Recommendations based on Incremental Tensor Reduction and Local PathTraversal”, Proceedings of the 3rdACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN),Chicago, Illinois, 2011
  27. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: “Geo-social Recommendations”, Proceedings of the RecSys Workshop Personalization on Mobile Applications (PeMA), Chicago, Illinois, 2011.
  28. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: “Predicting Links in Social Networks of Trust via Bounded Local Path Traversal”, Proceedings of the 3rd Conference on Computational Aspects of Social Networks (CASON), Salamanca, Spain, 2011.
  29. Z.F. Siddiqui, M.Spiliopoulou, P. Symeonidis, E. Tiakas: “A Data Generator for Multi-Stream Data”, Proceedings of the PKDD Workshop Mining Ubiquitous & Social Environments (MUSE), Athens, Greece, 2011
  30. P. Symeonidis, Y. Manolopoulos: “Explaining Recommendations of Movies in Web Video Rental Businesses”, Proceedings of the 2ndSymposium on Business Informatics in Central & Eastern Europe (CEE),Cluj-Napoca, Romania, 2011
  31. P.Symeonidis, E. Tiakas, Y. Manolopoulos: “Transitive Node similarity for Link Prediction in Social Networks with positive and negative links”, Proceedings of the 4th ACM Conference in Recommender Systems (RecSys), pp.183-190, Barcelona, 2010.
  32. N.Iakovidou, P. Symeonidis, Y. Manolopoulos: “Multiway Spectral Clustering Link Prediction in Protein-Protein Interaction Networks”, Proceedings of the 10th IEEE International Conference onInformation Technology & Applications in Biomedicine (ITAB), Corfu,2010.
  33. P.Symeonidis, A. Nanopoulos, Y. Manolopoulos: “MoviExplain: a Recommender Agent Providing Justified Recommendations”, Proceedings of the 3rd ACM Conference in Recommender Systems (RecSys), NewYork, 2009.
  34. P. Symeonidis: “User Recommendations based on Tensor Dimensionality Reduction”, Proceedings of the 5th IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI), pp.331-341,Thessaloniki, Greece, 2009.
  35. P. Symeonidis, A.Nanopoulos, Y. Manolopoulos: “Tag Recommendations based on Tensor Dimensionality Reduction”, Proceedings of the 2nd ACM Conference in Recommender Systems (RecSys),pp.43-50, Lausanne, 2008.
  36. P. Symeonidis, A.Nanopoulos, Y. Manolopoulos: “Justified Recommendations based on Content and Rating Data”, Proceedings of the 10th WebKDD Workshop in conjunction with KDD Conference, Las Vegas, NV, 2008.
  37. P. Symeonidis, M.Ruxanda, A. Nanopoulos, Y. Manolopoulos: “Ternary Semantic Analysis of Social Tags for Personalized Music Recommendation”, Proceedings of the 9th Annual Conference on MusicInformation Retrieval (ISMIR), pp.219-224, Philadelphia, 2008
  38. P.Symeonidis: “Content-based Dimensionality Reduction for Recommender Systems”, Proceedings of the 31st AnnualConference of the German Classification Society (GfKl), Freiburg, Germany,2007.
  39. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Feature-weighted User Model for Recommender Systems”, Proceedings of the 11thInternational Conference on User Modelling (UM), Vol.4511, pp.97-106,Corfu, Greece, 2007.
  40. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Collaborative Filtering: Fallacies and Insights in Measuring Similarity”, Proceedings of the Web Mining Workshop held in conjunction with PKDD/ECML conference, pp.56-67,Berlin, Germany, 2006.
  41. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Nearest-Biclusters Collaborative Filtering”, Proceedings of the WebKDD Workshop held in conjunction with KDD, pp.15-25, Philadelphia, PA, 2006.
  42. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Collaborative Filtering based on Users Trends”, Proceedings of the 30th Annual Conference of the German Classification Society (GfKl), pp.375-382, Berlin,Germany, 2006.
  43. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Collaborative Filtering Process in a Whole New Light”, Proceedings of the 10th International Symposium on Data Engineering & Applications (IDEAS), pp.29-36, Delhi, India, 2006.
  44. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: “Scalable Collaborative Filtering Based on Latent Semantic Indexing”, Proceedings of the AAAI Workshop on Intelligent Techniques for Web Personalization (ITWP),pp.1-9, Boston, MA, 2006.