{"id":68,"date":"2018-12-12T12:07:54","date_gmt":"2018-12-12T12:07:54","guid":{"rendered":"https:\/\/www.panagiotissymeonidis.com\/?page_id=68"},"modified":"2023-03-12T11:02:32","modified_gmt":"2023-03-12T11:02:32","slug":"publications-2","status":"publish","type":"page","link":"https:\/\/www.panagiotissymeonidis.com\/?page_id=68","title":{"rendered":"Publications"},"content":{"rendered":"\n

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Link to my Google Scholar Profile<\/a>.<\/h4>\n\n\n\n

International Books\/Monographs<\/h2>\n\n\n\n
    \n
  1. P. Symeonidis, A. Zioupos: \u201cMatrix and Tensor Factorization Techniques for Recommender Systems<\/em>\u201d, Series: Springer Briefs in Computer Science, 2017, 102 pages, 29 b\/w illustrations, 22 illustrations in colour, ISBN,978-3-319-41356-3 (DOI<\/a>)<\/li>\n\n\n\n
  2. P. Symeonidis, D. Ntempos, Y. Manolopoulos: \u201cRecommender Systems for Location-based Social Networks<\/em>\u201d, Series: Springer Briefs in Electrical and Computer Engineering, 2014, 118 pages, 41 illus., Softcover, ISBN 978-1-4939-0285-9 (DOI<\/a>)<\/li>\n\n\n\n
  3. L. Balby Marinho, A. Hotho, R. J\u00e4schke, A. Nanopoulos, S. Rendle, L. Schmidt-Thieme, G. Stumme, P. Symeonidis: \u201cRecommender Systems for Social Tagging Systems<\/em>\u201d, Series: SpringerBriefs in Electrical and Computer Engineering, 2012, 115 pages, 35 illus., Softcover, ISBN 978-1-4614-1893-1 (DOI<\/a>)<\/li>\n<\/ol>\n\n\n\n

    Greek Textbooks<\/h2>\n\n\n\n
      \n
    1. \u03a0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b7\u03c2 \u03a3\u03c5\u03bc\u03b5\u03c9\u03bd\u03af\u03b4\u03b7\u03c2, (2023). \u0395\u03c5\u03c6\u03c5\u03ae \u03a3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03a3\u03c5\u03c3\u03c4\u03ac\u03c3\u03b5\u03c9\u03bd. \u0391\u03b8\u03ae\u03bd\u03b1, \u039a\u03ac\u03bb\u03bb\u03b9\u03c0\u03bf\u03c2, \u0391\u03bd\u03bf\u03b9\u03ba\u03c4\u03ad\u03c2 \u0391\u03ba\u03b1\u03b4\u03b7\u03bc\u03b1\u03ca\u03ba\u03ad\u03c2 \u0395\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2. http:\/\/dx.doi.org\/10.57713\/kallipos-156 ISBN: 978-618-5726-37-9<\/li>\n\n\n\n
    2. \u03a0\u03b1\u03bd\u03b1\u03b3\u03b9\u03ce\u03c4\u03b7\u03c2 \u03a3\u03c5\u03bc\u03b5\u03c9\u03bd\u03af\u03b4\u03b7\u03c2, \u0393\u03bf\u03cd\u03bd\u03b1\u03c1\u03b7\u03c2 \u0391\u03bd\u03b1\u03c3\u03c4\u03ac\u03c3\u03b9\u03bf\u03c2, \u201c\u0392\u03ac\u03c3\u03b5\u03b9\u03c2 \u0391\u03c0\u03bf\u03b8\u03ae\u03ba\u03b5\u03c2 \u03ba\u03b1\u03b9 \u0395\u03be\u03cc\u03c1\u03c5\u03be\u03b7 \u0394\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd: \u03a3\u03c4\u03bf \u0395\u03c1\u03b3\u03b1\u03c3\u03c4\u03ae\u03c1\u03b9\u03bf \u03bc\u03b5 \u03c4\u03bf\u03bd SQL Server<\/em>\u201d, \u0391\u03b8\u03ae\u03bd\u03b1: \u03a3\u03cd\u03bd\u03b4\u03b5\u03c3\u03bc\u03bf\u03c2 \u0395\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ce\u03bd \u0391\u03ba\u03b1\u03b4\u03b7\u03bc\u03b1\u03ca\u03ba\u03ce\u03bd \u0392\u03b9\u03b2\u03bb\u03b9\u03bf\u03b8\u03b7\u03ba\u03ce\u03bd. ISBN: 978-960-603-021-5 (DOI<\/a>)<\/li>\n<\/ol>\n\n\n\n

      Journal Publications<\/h2>\n\n\n\n
        \n
      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.<\/li>\n\n\n\n
      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<\/a><\/li>\n\n\n\n
      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.<\/li>\n\n\n\n
      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) <\/em>58(2): 223-225 (2022)<\/li>\n\n\n\n
      5. Symeonidis, P., Kirjackaja, L., Zanker, M. \u201cSession-based News Recommendations using SimRank on multi-modal Graphs\u201d, Expert Systems with Applications (Elsevier), <\/em>2021  <\/em>https:\/\/doi.org\/10.1016\/j.eswa.2021.115028<\/a><\/li>\n\n\n\n
      6. Berbague, C., Karabadji, N., Seridi, H., Symeonidis, P., Manolopoulos, Y., Dhifli, W. \u201cAn overlapping clustering approach for precision, and novelty-aware recommendation\u201d, Expert Systems with Applications <\/em>(Elsevier) vol. 177, 2021<\/li>\n\n\n\n
      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<\/em> (8) pages: 181835-181847 (2020)<\/li>\n\n\n\n
      8. Symeonidis, P., Kirjackaja, L., Zanker, M. \u201cSession\u2011aware news recommendations using random walks on time\u2011evolving heterogeneous information networks\u201d, User Modelling and User-Adapted Interaction, <\/em>https:\/\/doi.org\/10.1007\/s11257-020-09261-9<\/a>, 2020<\/li>\n\n\n\n
      9. P. Symeonidis, L. Coba, M. Zanker: \u201cPersonalized Novel and Explainable Matrix Factorization\u201d, Data and Knowledge Engineering Journal, Elsevier (accepted for publication in June 2019)<\/li>\n\n\n\n
      10. P. Symeonidis, L. Coba, M. Zanker: \u201cCounteracting the Filter Bubble in Recommender Systems: Novelty-aware Matrix Factorization, Intelligenza Artificiale, IOS Press (accepted for publication in June 2019)<\/li>\n\n\n\n
      11. P. Kefalas, P. Symeonidis, Y. Manolopoulos: \u201cRecommendations based on a Heterogeneous Spatio-temporal Social Network\u201d, World Wide Web<\/em>, Vol. 21,N. 2, pp. 345-371, 2017. (Impact factor in 2017: 1.405)<\/strong><\/li>\n\n\n\n
      12. P. Symeonidis, D. Malakoiudis: \u201cMulti-Modal Matrix Factorization with Side Information for Recommending Massive Open Online Courses\u201d, Expert Systems with Applications, Vol. 118, pp. 261 \u2013 271, 2019, DOI:https:\/\/doi.org\/10.1016\/j.eswa.2018.09.053<\/li>\n\n\n\n
      13. P. Kefalas, P. Symeonidis, Y. Manolopoulos: \u201cA Graph-based Taxonomy of Recommendation Algorithms and Systems in LBSNs\u201d, IEEE Transactions on Knowledge & Data Engineering<\/em>, Vol.28, N.3, pp. 604-622, 2016. (Impact factor in 2016: 3.438) <\/strong><\/li>\n\n\n\n
      14. P. Symeonidis: \u201cClustHOSVD: Item Recommendation by Combining Semantically-enhanced Tag Clustering with Tensor HOSVD\u201d, IEEE Transactions on Systems, Man & Cybernetics – Part A: Systems<\/em> &Humans<\/em>, Vol. 46, No. 9, 2016. (Impact factor in 2016: 2.350)<\/strong><\/li>\n\n\n\n
      15. M. Sattari, I. Toroslu, P. Karagoz, P. Symeonidis, Y. Manolopoulos: \u201cExtended Feature Combination Model forRecommendations in Location-based Mobile Services\u201d, Knowledge & Information Systems<\/em>, Vol.3, N.44, pp. 629-661,2015. (Impact factor in 2015: 1.702)<\/strong><\/li>\n\n\n\n
      16. Z.F. Siddiqui, E. Tiakas, P. Symeonidis, M. Spiliopoulou, Y. Manolopoulos: \u201cLearning Relational User Profiles and Recommending Items as their Preferences Change\u201d, International Journal of AI Tools,<\/em> Vol.24, N.2, 2015 (impact factor in 2015: 0.530)<\/strong><\/li>\n\n\n\n
      17. P. Symeonidis, E. Tiakas: \u201cTransitive Node Similarity: Predicting and Recommending Links in Signed Social Networks\u201d, World Wide Web<\/em>, Vol.17, No.4, pp.743-776, 2014. (impact factor in 2014: 1.474)<\/strong><\/li>\n\n\n\n
      18. P. Symeonidis, E. Tiakas, Y. Manolopoulos: \u201cA Unified Framework for Link and Rating Prediction in Multi-modal SocialNetworks\u201d, International Journal ofSocial Network Mining<\/em>, Vol.1, No.3\/4, 2013.<\/li>\n\n\n\n
      19. P. Symeonidis, N. Mantas: \u201cSpectral Clustering for Link Prediction in Social Networks with Positive and Negative Links\u201d, Social Network Analysis & Mining<\/em>, Vol.3, No.4, pp.1433-1447, 2013. (impact factor in 2013: 0.503)<\/strong><\/li>\n\n\n\n
      20. P.Symeonidis, N. Iakovidou, N. Mantas, Y. Manolopoulos: \u201cFrom Biological to Social Networks: Link prediction based on Multi-way Spectral Clustering\u201d, Data & Knowledge Engineering<\/em>, Vol.87, pp.226-242, 2013. (impact factor in 2013: 1.489)<\/strong><\/li>\n\n\n\n
      21. P. Longinidis, P. Symeonidis: \u201cCorporate Dividend Policy Determinants: Intelligent versus a Traditional Approach\u201d, Intelligent Systems in Accounting, Finance & Management<\/em>, Vol.20, No.2, pp.111-139, 2013.<\/li>\n\n\n\n
      22. A. Papadimitriou, P. Symeonidis, Y. Manolopoulos: \u201cFast and Accurate Link Prediction in Social Networking Systems\u201d, Journal of Systems & Software<\/em>, Vol.85, No.9, pp.2119-2132, 2012. (impact factor in 2012: 1.135)<\/strong><\/li>\n\n\n\n
      23. A. Papadimitriou, P. Symeonidis, Y. Manolopoulos: \u201cA Generalized Taxonomy of Explanations Styles for Traditional and Social Recommender Systems\u201d, Data Mining & Knowledge Discovery<\/em>, pp.1-29, 2011. (impact factor in 2011:1.545)<\/strong><\/li>\n\n\n\n
      24. P. Symeonidis, A. Nanopoulos, Y. Manolopoulos: \u201cA Unified Framework for Providing Recommendations in Social Tagging Systems Based on Ternary Semantic Analysis\u201d, IEEE Transactions on Knowledge & Data Engineering<\/em>, Vol.22, No.2, 2010. (impact factor in 2010: 1.851)<\/strong><\/li>\n\n\n\n
      25. A.Nanopoulos, D. Rafailidis, P. Symeonidis, Y. Manolopoulos: \u201cMusicBox: Personalized Music Recommendation based on Cubic Analysis of Social Tags\u201d, IEEE Transactions on Audio, Speech &Language Processing<\/em>, Vol.18, No.2, 2010. (impact factor in 2010: 1.668)<\/strong><\/li>\n\n\n\n
      26. A. Deligiaouri, P. Symeonidis: \u201cSkai (TV) – YouTube Debate\u201d: A New Era of Internetized Television Politics\u201d, International Journal of E-Politics<\/em>, Vol.1, No.2, 2010 (publisher: IGI global).<\/li>\n\n\n\n
      27. P. Symeonidis, A. Deligiaouri: \u201cRecommending Posts in Political Blogs based on Tensor Dimensionality Reduction\u201d, International Journal of Engineering Intelligent Systems<\/em>, Vol.17, No.2-3, 2009. (impact factor in 2009: 0.205)<\/strong><\/li>\n\n\n\n
      28. P. Symeonidis, A. Nanopoulos, Y. Manolopoulos: \u201cProviding Justifications in Recommender Systems\u201d, IEEE Transactions on Systems, Man & Cybernetics – Part A: Systems & Humans<\/em>, Vol.38, No.6, 2008. (impactfactor in 2008: 1.350)<\/strong><\/li>\n\n\n\n
      29. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cNearest-biclusters Collaborative Filtering with Constant and Coherent Values\u201d, Information Retrieval<\/em>, Vol.11, No.1, 2008. (5-year impact factor in 2008: 1.396)<\/strong><\/li>\n\n\n\n
      30. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cCollaborative Filtering Systems: Combining Effectiveness and Efficiency\u201d, Expert Systems with Applications<\/em>, Vol.34, No.4, pp.51-75, 2008. (impact factor in 2008: 2.596)<\/strong><\/li>\n<\/ol>\n\n\n\n

        Book Chapters<\/h2>\n\n\n\n
          \n
        1. G. Sottocornola, F. Stella, P. Symeonidis, M. Zanker, I. Krajger, R. Faullant, and E. Schwarz: Identifying Innovative Idea Proposals with Topic Models\u2014A 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<\/li>\n\n\n\n
        2. P. Symeonidis, D. Malakoudis: \u201cMoocRec.com: Massive Open Online Courses recommender system\u201d chapter in the book entitled \u201cCollaborative Recommendations: Algorithms, Practical Challenges and Applications<\/em>\u201d (to appear in the end of 2018).<\/li>\n\n\n\n
        3. P. Symeonidis: \u201cMatrix and Tensor Factorization in Recommender Systems\u201d, chapter in the book entitled \u201cGraph-based Social Media Analysis<\/em>\u201d, by I. Pitas (ed.), CRC Press, Taylor & Francis group, Chapman & Hall\/CRC, pp. 187-210, 2015, 2015.<\/li>\n\n\n\n
        4. L. Marinho, A. Nanopoulos, L. Schmidt-Thieme, R. Jaschke, A. Hotho, G.Stumme, P. Symeonidis: \u201cSocial Tagging Recommender Systems\u201d, chapter in book entitled \u201cRecommender Systems Handbook<\/em>\u201d, by F. Ricci, L. Rokach, B. Shaphira, P.B. Kantor (eds.): LNCS Springer Book, pp. 615-644, 2011.<\/li>\n\n\n\n
        5. A. Deligiaouri, P. Symeonidis: \u201cInternetized Television Debates: Enhancing Citizens\u2019 Participation\u201d, chapter in book entitled \u201cE-Politics and Organizational Implications of the Internet: Power, Influence and Social Change<\/em>\u201d by C.R. Livermore (ed.), IGI Global, 2011.<\/li>\n\n\n\n
        6. P. Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cNearest-biclusters Collaborative Filtering based on constant values\u201d, chapter in book entitled \u201cAdvances in Web Mining and Web Usage Analysis<\/em>\u201d, by O. Nasraoui, O. Zaiane, M. Spiliopoulou, M.Mobasher, B. Masand, P. Yu (eds.), LNCS Springer, Vol.4811, pp.36-55, 2007.<\/li>\n<\/ol>\n\n\n\n

          Conference Papers<\/h2>\n\n\n\n
            \n
          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.<\/li>\n\n\n\n
          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.<\/li>\n\n\n\n
          3. Symeonidis, P., Kirjackaja, L., Zanker, M. \u201cSession-based Recommendation along with the Session Style of Explanation\u201d, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML\/PKDD), pp. 147-162, Grenoble France, 2022<\/li>\n\n\n\n
          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<\/li>\n\n\n\n
          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<\/li>\n\n\n\n
          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<\/li>\n\n\n\n
          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<\/li>\n\n\n\n
          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<\/li>\n\n\n\n
          9. L. Coba, M. Zanker, L. Rook, P. Symeonidis: \u201cDecision Making Strategies Differ in the Presence of Collaborative Explanations: Two Conjoint Studies\u201d Proceedings of the 24th<\/sup>International Conference on Intelligent User Interfaces, (to appear), Los Angeles, 2019.<\/li>\n\n\n\n
          10. G. Sottocornola, P. Symeonidis, M. Zanker: \u201cSession-based News Recommendations\u201d, Companion Proceedings of  The Web Conference 2018, <\/em>pp. 1395-1399, 2018.
            International World Wide Web Conferences Steering Committee.<\/li>\n\n\n\n
          11. L. \u00c7oba, P.Symeonidis, M. Zanker: \u201cReplicating and Improving Top-N Recommendations in Open Source Packages\u201d, Proceedings of the 8th <\/sup>International Conference on Web Intelligence, Mining and Semantics (WIMS), <\/em>Novi Sad, Serbia, 2018.<\/li>\n\n\n\n
          12. L. Coba, M. Zanker, L.Rook, P. Symeonidis: \u201cExploring Users\u2019 Perception of Rating Summary Statistics\u201d, Proceedings of the 26th<\/sup> Conferenceon User Modeling, Adaptation and Personalization (UMAP),<\/em> 2018.<\/li>\n\n\n\n
          13. L. \u00c7oba, P. Symeonidis, M. Zanker: \u201cReproducing and Prototyping Recommender Systems in R\u201d, Proceedings of the 8th<\/sup> Italian Information Retrieval Workshop<\/em>, 2017<\/li>\n\n\n\n
          14. L. \u00c7oba, P.Symeonidis, M. Zanker: \u201cVisual Analysis of Recommendation Performance\u201d, Proceedings of the 11th<\/sup> ACM Conference on Recommender Systems (RecSys), <\/em>pp.362-363, 2017.<\/li>\n\n\n\n
          15. P. Symeonidis, S. Chairistanidis: \u201cCheckInShop.eu: A Sensor-based Recommender System for micro-location Marketing\u201d, Proceedings ofthe 11th<\/sup> ACM Conference on Recommender Systems (RecSys),<\/em> pp.351-352,2017<\/li>\n\n\n\n
          16. P. Symeonidis: \u201cMatrix and Tensor Decomposition in Recommender Systems\u201d, Tutorial Presentation at ACM RecSys’2016 conference, September 2016, Boston, MA.<\/li>\n\n\n\n
          17. P. Kefalas, P.Symeonidis: \u201cRecommending Friends and Locations over a Heterogeneous Spatio-temporal Graph\u201d, Proceedings of the 5th<\/sup>International Conference on Model & Data Engineering (MEDI), <\/em>pp.271-284, Island of Rhodes, Greece, 2015.<\/li>\n\n\n\n
          18. P. Symeonidis, C. Perentis: \u201cLink Prediction in Multi-modal Social Networks\u201d, Proceedings of the International Conference on Machine Learning & Knowledge Discovery in Databases (ECML\/PKDD), <\/em>pp. 147-162, Nancy France, 2014<\/li>\n\n\n\n
          19. Z.F. Siddiqui, E.Tiakas, P. Symeonidis, M. Spiliopoulou, Y. Manolopoulos: \u201cxStreams: Providing Item Recommendations to Users with Time-evolving Preferences\u201d, Proceedings of the 4th<\/sup>International Conference on Web Intelligence, Mining & Semantics (WIMS),<\/em>Thessaloniki, Greece, 2014.<\/li>\n\n\n\n
          20. P. Kefalas, P. Symeonidis, Y. Manolopoulos: \u201cNew Perspectives for Recommendations in Location-based Social Networks: Time, Privacy and Explainability\u201d, Proceedings of the 5th<\/sup>International Conference on Management of Emergent Digital EcoSystems (MEDES), <\/em>pp.1-8, Neumuenster Abbey, Luxembourg, 2013.<\/li>\n\n\n\n
          21. P. Symeonidis, A.Krinis, Y. Manolopoulos: \u201cGeoSocialRec: Explaining Recommendations in Location-based Social Networks\u201d, Proceedings of the 17th<\/sup> East-European Conference on Advanced Databases & Information Systems (ADBIS),<\/em> pp. 84-97, Genova, Italy, 2013.<\/li>\n\n\n\n
          22. P. Symeonidis., I.Kehayov, Y. Manolopoulos: \u201cText Classification by Aggregation of SVD Eigenvectors\u201d, Proceedings of the 16th<\/sup>East-European Conference on Advances in Databases & Information Systems(ADBIS),<\/em> pp.385-398, Poznan, Poland, 2012.<\/li>\n\n\n\n
          23. M. Sattari, I.Toroslu, P. Senkul, M. Manguoglu, P. Symeonidis, Y. Manolopoulos: \u201cGeo-activityRecommendations by using Improved Feature Combination\u201d, Proceedings of the 4th<\/sup> ACM UNICOMP International Workshop onLocation-Based Social Networks (LBSN),<\/em> Pittsburgh, PA, 2012.<\/li>\n\n\n\n
          24. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: \u201cScalable Link Prediction in Social Networks based on Local Graph Characteristics\u201d, Proceedings of the 9th<\/sup> International Conference on Information Technology: NewGenerations (ITNG),<\/em> Las Vegas, NV, 2012<\/li>\n\n\n\n
          25. P. Symeonidis, E.Tiakas, Y. Manolopoulos: \u201cProduct Recommendation and Rating Prediction based onMulti-modal Social Networks\u201d, Proceedings of the 5th<\/sup> ACM Conference in Recommender Systems (RecSys), <\/em>Chicago,IL, 2011.<\/li>\n\n\n\n
          26. P. Symeonidis, A.Papadimitriou, Y. Manolopoulos, P. Senkul, I. Toroslu: \u201cGeo-social Recommendations based on Incremental Tensor Reduction and Local PathTraversal\u201d, Proceedings of the 3rd<\/sup>ACM SIGSPATIAL International Workshop on Location-Based Social Networks (LBSN),<\/em>Chicago, Illinois, 2011 <\/li>\n\n\n\n
          27. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: \u201cGeo-social Recommendations\u201d, Proceedings of the RecSys Workshop Personalization on Mobile Applications (PeMA),<\/em> Chicago, Illinois, 2011.<\/li>\n\n\n\n
          28. A. Papadimitriou, P.Symeonidis, Y. Manolopoulos: \u201cPredicting Links in Social Networks of Trust via Bounded Local Path Traversal\u201d, Proceedings of the 3rd<\/sup> Conference on Computational Aspects of Social Networks (CASON), <\/em>Salamanca, Spain, 2011.<\/li>\n\n\n\n
          29. Z.F. Siddiqui, M.Spiliopoulou, P. Symeonidis, E. Tiakas: \u201cA Data Generator for Multi-Stream Data\u201d, Proceedings of the PKDD Workshop Mining Ubiquitous & Social Environments (MUSE), <\/em>Athens, Greece, 2011 <\/li>\n\n\n\n
          30. P. Symeonidis, Y. Manolopoulos: \u201cExplaining Recommendations of Movies in Web Video Rental Businesses\u201d, Proceedings of the 2nd<\/sup>Symposium on Business Informatics in Central & Eastern Europe (CEE),<\/em>Cluj-Napoca, Romania, 2011<\/li>\n\n\n\n
          31. P.Symeonidis, E. Tiakas, Y. Manolopoulos: \u201cTransitive Node similarity for Link Prediction in Social Networks with positive and negative links\u201d, Proceedings of the 4th<\/sup> ACM Conference in Recommender Systems<\/em> (RecSys), pp.183-190, Barcelona, 2010.<\/li>\n\n\n\n
          32. N.Iakovidou, P. Symeonidis, Y. Manolopoulos: \u201cMultiway Spectral Clustering Link Prediction in Protein-Protein Interaction Networks\u201d, Proceedings of the 10th<\/sup> IEEE International Conference onInformation Technology & Applications in Biomedicine (ITAB),<\/em> Corfu,2010.<\/li>\n\n\n\n
          33. P.Symeonidis, A. Nanopoulos, Y. Manolopoulos: \u201cMoviExplain: a Recommender Agent Providing Justified Recommendations\u201d, Proceedings of the 3rd<\/sup> ACM Conference in Recommender Systems (RecSys),<\/em> NewYork, 2009.<\/li>\n\n\n\n
          34. P. Symeonidis: \u201cUser Recommendations based on Tensor Dimensionality Reduction\u201d, Proceedings of the 5th<\/sup> IFIP Conference on Artificial Intelligence Applications & Innovations <\/em>(AIAI), <\/strong>pp.331-341,Thessaloniki, Greece, 2009.<\/li>\n\n\n\n
          35. P. Symeonidis, A.Nanopoulos, Y. Manolopoulos: \u201cTag Recommendations based on Tensor Dimensionality Reduction\u201d, Proceedings of the 2nd<\/sup> ACM Conference in Recommender Systems<\/em> (RecSys),pp.43-50, Lausanne, 2008.<\/li>\n\n\n\n
          36. P. Symeonidis, A.Nanopoulos, Y. Manolopoulos: \u201cJustified Recommendations based on Content and Rating Data\u201d, Proceedings of the 10th<\/sup> WebKDD Workshop in conjunction with KDD Conference<\/em>, Las Vegas, NV, 2008.<\/li>\n\n\n\n
          37. P. Symeonidis, M.Ruxanda, A. Nanopoulos, Y. Manolopoulos: \u201cTernary Semantic Analysis of Social Tags for Personalized Music Recommendation”, Proceedings of the 9th<\/sup> Annual Conference on MusicInformation Retrieval (ISMIR),<\/em> pp.219-224, Philadelphia, 2008 <\/li>\n\n\n\n
          38. P.Symeonidis: \u201cContent-based Dimensionality Reduction for Recommender Systems\u201d, Proceedings of the 31st<\/sup> AnnualConference of the German Classification Society<\/em> (GfKl), Freiburg, Germany,2007.<\/li>\n\n\n\n
          39. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cFeature-weighted User Model for Recommender Systems\u201d, Proceedings of the 11th<\/sup>International Conference on User Modelling (UM)<\/em>, Vol.4511, pp.97-106,Corfu, Greece, 2007. <\/li>\n\n\n\n
          40. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cCollaborative Filtering: Fallacies and Insights in Measuring Similarity\u201d, Proceedings of the Web Mining Workshop held in conjunction with PKDD\/ECML conference<\/em>, pp.56-67,Berlin, Germany, 2006.<\/li>\n\n\n\n
          41. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cNearest-Biclusters Collaborative Filtering\u201d, Proceedings of the WebKDD Workshop held in conjunction with KDD<\/em>, pp.15-25, Philadelphia, PA, 2006. <\/li>\n\n\n\n
          42. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cCollaborative Filtering based on Users Trends\u201d, Proceedings of the 30th<\/sup> Annual Conference of the German Classification Society (GfKl)<\/em>, pp.375-382, Berlin,Germany, 2006.<\/li>\n\n\n\n
          43. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cCollaborative Filtering Process in a Whole New Light\u201d, Proceedings of the 10th<\/sup> International Symposium on Data Engineering & Applications (IDEAS), <\/em>pp.29-36, Delhi, India, 2006.<\/li>\n\n\n\n
          44. P.Symeonidis, A. Nanopoulos, A. Papadopoulos, Y. Manolopoulos: \u201cScalable Collaborative Filtering Based on Latent Semantic Indexing\u201d, Proceedings of the AAAI Workshop on Intelligent Techniques for Web Personalization (ITWP)<\/em>,pp.1-9, Boston, MA, 2006.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

            Link to my Google Scholar Profile. International Books\/Monographs Greek Textbooks Journal Publications Book Chapters Conference Papers<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-68","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/pages\/68","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=68"}],"version-history":[{"count":19,"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/pages\/68\/revisions"}],"predecessor-version":[{"id":598,"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=\/wp\/v2\/pages\/68\/revisions\/598"}],"wp:attachment":[{"href":"https:\/\/www.panagiotissymeonidis.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=68"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}