{"id":77,"date":"2018-02-12T09:09:44","date_gmt":"2018-02-12T09:09:44","guid":{"rendered":"https:\/\/trackandknowproject.eu\/?page_id=77"},"modified":"2021-06-17T13:50:34","modified_gmt":"2021-06-17T12:50:34","slug":"scientific-publications","status":"publish","type":"page","link":"https:\/\/trackandknowproject.eu\/publications\/scientific-publications\/","title":{"rendered":"Scientific publications"},"content":{"rendered":"\n

Journal publications<\/h4>\n\n\n\n

Mobility-based Big Data: Integration and Processing<\/strong><\/p>\n\n\n\n

  1. Tampakis, P., Doulkeridis, C., Pelekis, N., Theodoridis, Y. 2020. \u201cDistributed Subtrajectory Join on Massive Datasets.\u201d ACM Digital Library. Click here for the published version.<\/a><\/li>
  2. Fu, C., Huang, H., & Weibel, R. 2020. Adaptive simplification of GPS trajectories with geographic context\u2013a quadtree-based approach. International Journal of Geographical Information Science, 1-28. Click here for the published version.<\/a><\/li>
  3. Doulkeridis, C. 2020. Scalable Enrichment of Mobility Data with Weather Information, GeoInformatica. Click here for the published version.<\/a><\/li><\/ol>\n\n\n\n
    \n\n\n\n

    Mobility-based<\/strong> Big Data: Analytics<\/strong><\/p>\n\n\n\n

    1. Longhi L., Nanni M., \u201cCar telematics big data analytics for insurance and innovative mobility services\u201d, Journal of Ambient Intelligence and Humanized Computing (2019)\u00a0Click here for the pre-published version<\/a><\/li>
    2. Adnan, M., Gazder, U., Yasar, A.-u.-H., Bellemans, T. & Kureshi, I. 2020. \u201cEstimation of travel time distributions for urban roads using GPS trajectories of vehicles: a case of Athens, Greece.\u201d Personal and Ubiquitous Computing.\u00a0
      Click here for the published version.<\/a><\/li>
    3. Liu, F., Andrienko, G., Andrienko, N., Chen, S., Janssens, D., Wets, G., Theodoridis, Y. 2020. “Citywide traffic analysis based on the combination of visual and analytic approaches.”
      Click here for the published version.<\/a><\/li>
    4. Andrienko, N., Andrienko, G. “Spatio-temporal visual analytics: a vision for 2020s.” Journal of Spatial Information Science, 2020, number 20, pp.87-95.
      Click here for the published version.<\/a><\/li>
    5. Nanni, M., Tortosa, L., Vicent, J., Yeghikyan, G. “Ranking places in attributed temporal urban mobility networks.” PLoS ONE, 2020, 15(10): e0239319.
      Click here for the published version.<\/a><\/li>
    6. Andrienko, G., Andrienko, N., Kureshi, I., Lee, K., Smith, I., Staykova, T. “Automating and utilizing equal-distribution data classification.” International Journal of Cartography,\u00a02020.
      Click here for the published version.<\/a><\/li><\/ol>\n\n\n\n
      \n\n\n\n

      Mobility-based<\/strong> Big Data: Visual Analytics<\/strong><\/p>\n\n\n\n

      1. Markovic, N., Sekula, P., Vander Laan, Z., Andrienko, G., Andrienko, N. (2018). Applications of Trajectory Data From the Perspective of a Road Transportation Agency: Literature Review and Maryland Case Study.\u00a0IEEE Transactions on Intelligent Transportation Systems (Early Access)<\/em>, 1-12. doi.org\/10.1109\/TITS.2018.2843298<\/avayaelement><\/avayaelement>.
        Click here for the pre-print version in open access.<\/a><\/li>
      2. Christopher Collins, Natalia Andrienko, Tobias Schreck, Jing Yang, Jaegul Choo, Ulrich Engelke, Amit Jena, Tim Dwyer, \u201cGuidance in the human-machine analytics process\u201d, Visual Informatics, 2018, vol. 2(3), pp.166-180. Click here for the published version.\u00a0\u00a0<\/a><\/li>
      3. Jie Li, Siming Chen, Kang Zhang, Gennady Andrienko, and Natalia Andrienko, \u201cCOPE: Interactive Exploration of Co-occurrence Patterns in Spatial Time Series\u201d,\u00a0IEEE Transactions on Visualization and Computer Graphics, 2018.
        Click here for the pre-print version. <\/a>
        Click here for the published version.\u00a0<\/a><\/li>
      4. Shixia Liua, Gennady Andrienko, Yingcai Wu, Nan Cao, Liu Jiang, Conglei Shi, Yu-Shuen Wang, Seokhee Hong, \u201cSteering Data Quality with Visual Analytics: the Complexity Challenge\u201d, Visual Informatics, 2019.
        Click here for the published version.<\/a><\/li>
      5. Tritsarolis A, Theodoropoulos GS, Theodoridis Y (2020). “Online discovery of co-movement patterns in mobility data.” Int. J. Geographical Information Science, Taylor & Francis.\u00a0
        Click here for the published version. <\/a><\/li><\/ol>\n\n\n\n
        \n\n\n\n

        Conference publications<\/h4>\n\n\n\n

        Mobility-based<\/strong> Big Data: Integration and Processing<\/strong><\/p>\n\n\n\n

        1. Koutroumanis N., Santipantakis G., Glenis A., Doulkeridis C.,Vouros G. , \u201cIntegration of Mobility Data with Weather Information\u201d,\u00a0<\/em>EDBT\/ICDT workshops 2019,<\/em>\u00a0Lisbon, Portugal, 2019.
          Click here to download. <\/a><\/li>
        2. P. Nikitopoulos, G.A. Sfyris, A. Vlachou, C. Doulkeridis, O. Telelis:\u00a0\u201cParallel and Distributed Processing of Reverse Top-k Queries\u201d, In\u00a0Proceedings of the 35th IEEE International Conference on Data\u00a0Engineering (ICDE 2019). Click here for the published version.<\/a><\/li>
        3. Koutroumanis N., Nikitopoulos P., Vlachou A., Doulkeridis C. (2019): NoDA: Unified NoSQL Data Access Operators for Mobility Data. In:\u00a0Proceedings of the 16th International Symposium on Spatial and Temporal Databases (SSTD\u201919)<\/em>. Click here for the published version.<\/a><\/li>
        4. Nikitopoulos, P., Sfyris, G.A., Vlachou, A., Doulkeridis, C., Telelis, O. “Pruning Techniques for Parallel Processing of Reverse Top-k Queries.” Distributed and Parallel Databases (Springer), 2020.
          Click here for the published version<\/a> (DOI 10.1007\/s10619-020-07297-9) <\/li>
        5. Fu, C., & Weibel, R. (2019, November). “Cross-scale Spatial Enrichment of Trajectories for Speeding Up Similarity Computing.” In 15th International Conference on Location-Based Services (p. 135). Click here for the published version. <\/a><\/li><\/ol>\n\n\n\n
          \n\n\n\n

          Mobility-based<\/strong> Big Data: Analytics<\/strong><\/p>\n\n\n\n

          1. P. Nikitopoulos, A.-I. Paraskevopoulos, C. Doulkeridis, N. Pelekis, Y. Theodoridis, \u201cHot Spot Analysis over Big Trajectory Data\u201d, In Proceedings of the 2018 IEEE International Conference on Big Data (IEEE BigData 2018).
            Click here to download. <\/a><\/li>
          2. Katzouris, N., Michelioudakis, E., Artikis, A., & Paliouras, G. (2018, September). Online learning of weighted relational rules for complex event recognition. In:\u00a0Joint European Conference on Machine Learning and Knowledge Discovery in Databases<\/em>\u00a0(pp. 396-413). Springer, Cham.
            Click here to download.<\/a><\/li>
          3. Guidotti, R, Monreale A, Cariaggi L (2019). Investigating Neighborhood Generation Methods for Explanations of Obscure Image-Classifiers, In: Yang Q., Zhou ZH., Gong Z., Zhang ML., Huang SJ. (eds) Advances in\u00a0Knowledge Discovery and Data Mining. PAKDD 2019. Lecture Notes in Computer Science, vol 11439.<\/em>\u00a0Springer, Cham.
            Click here for the published version.\u00a0<\/a> <\/li>
          4. Tsilionis E., Koutroumanis N., Nikitopoulos P., Doulkeridis C., Artikis A. (2019): Online Event Recognition from Moving Vehicle. In:\u00a0Proceedings of the 35th International Conference on Logic Programming (ICLP\u201919).<\/em>\u00a0Click here for the published version.<\/a><\/li>
          5. Nanni, M., Longhi, L. (2019): Vehicle mobility data analysis and Individual Mobility Networks for crash prediction.\u00a0
            Click here for the published version.<\/a><\/li>
          6. Theodoridis Y. (2020): Learning from Our Movements \u2013 The Mobility Data Analytics Era. In:\u00a0Tserpes K., Renso C., Matwin S. (eds) Multiple-Aspect Analysis of Semantic Trajectories. MASTER 2019. Lecture Notes in Computer Science, vol 11889. Springer, Cham.\u00a0<\/em>
            Click here for the published version.<\/a><\/li>
          7. Guidotti, R., Nanni, M. (2020). Crash Prediction and Risk
            Assessment with Individual Mobility Networks. The 21st IEEE International Conference on Mobile Data Management\u00a0 (MDM 2020).             Click here for the published version.<\/a><\/li>
          8. Yeghikyan, G., Opolka, F., Lepri, B., Nanni, M., Lio, P. Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks. 2020 IEEE International Conference on Smart Computing (SMARTCOMP). Click here for the published version.<\/a><\/li>
          9. Agnese Bonavita, Riccardo Guidotti, Mirco Nanni. “Self-Adapting Trajectory Segmentation.” In EDBT\/ICDT Workshop on Big Mobility Data Analytics (BMDA 2020), CEUR, vol 2578, 2020.
            Click here for the published version.<\/a><\/li>
          10. Tampakis P, Pelekis\u00a0N, Doulkeridis C, Theodoridis Y (2019) Scalable distributed sub-trajectory\u00a0clustering. Proceedings of\u00a0IEEE Big Data, Los Angeles \u2013 CA, USA. Click here for the published version.<\/a><\/li>
          11. Riccardo Guidotti, Mirco Nanni, Francesca Sbolgi. “Data-Driven Location Annotation for Fleet Mobility Modeling.” In EDBT\/ICDT Workshop on Big Mobility Data Analytics (BMDA 2020), CEUR, vol 2578, 2020. Click here for the published version.<\/a><\/li>
          12. Omid Isfahani Alamdari, Mirco Nanni, Roberto Trasarti, Dino Pedreschi. “Towards In-Memory Sub-Trajectory Similarity Search.” In EDBT\/ICDT Workshop on Big Mobility Data Analytics (BMDA 2020), CEUR, vol 2578, 2020. Click here for the published version.<\/a><\/li>
          13. Petros Petrou, Panagiotis Nikitopoulos, Panagiotis Tampakis, Apostolos Glenis, Nikolaos Koutroumanis, Georgios M. Santipantakis, Kostas Patroumpas, Akrivi Vlachou, Harris V. Georgiou, Eva Chondrodima, Christos Doulkeridis, Nikos Pelekis, Gennady L. Andrienko, Fabian Patterson, Georg Fuchs, Yannis Theodoridis, George A. Vouros: ARGO: A Big Data Framework for Online Trajectory Prediction. SSTD 2019: 194-197.
            Click here for the published version. <\/a><\/li>
          14. Katzouris N. and Artikis A.,\u00a0WOLED: A Tool for Online Learning Weighted Answer Set Rules for Temporal Reasoning Under Uncertainty.<\/em> In\u00a0Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning (KR)<\/em>, 2020. Click here for the published version.<\/a><\/li><\/ol>\n\n\n\n
            \n\n\n\n

            Mobility-based Big Data: Visual Analytics<\/strong><\/p>\n\n\n\n

            1. Andrienko N., Andrienko G., Garcia J. M. C., Scarlatti D. , \u201cAnalysis of Flight Variability: a Systematic Approach\u201d, IEEE Transactions on Visualization and Computer Graphics (proceedings IEEE VAST 2018), 2019, vol. 25(1), pp.54-64.
              Click here for the pre-print version.<\/a>
              Click here for the published version.<\/a>
              Video and supplementary material available via               https:\/\/ieeexplore.ieee.org\/document\/8440121\/media<\/a>\u00a0and\u00a0http:\/\/geoanalytics.net\/and\/papers\/vast18appendix.pdf<\/a><\/li>
            2. Tampakis P., Pelekis N., Andrienko N.V., Andrienko G. L., Fuchs G. , and Theodoridis Y. (2018) \u201cTime-aware sub-trajectory clustering in hermes@postgresql\u201d. In ICDE, pages 1581\u20131584, 2018. Click here for the published version.<\/a><\/li>
            3. Chen S., Andrienko G., Andrienko N., Doulkeridis C., Koumparos A., (2019) Contextualized Analysis of Movement Events, In: T. V. Landesberger and C.Turkay (Eds)\u00a0EuroVis Workshop on Visual Analytics (EuroVA)<\/em>, pp: 49- 53, The Eurographics Association. ISBN: 978-3-03868-087-1, DOI: 10.2312\/eurova.20191124.
              Click here to download<\/a> (This publication received the \u201cEUROVA 2019 best paper award\u201d)<\/strong><\/a><\/li><\/ol>\n\n\n\n
              \n\n\n\n

              Books<\/h4>\n\n\n\n
              1. Andrienko, G., Andrienko, N., Patterson, F., Chen, S., Weibel, R., Huang, H., Doulkeridis, C., Georgiou, H., Pelekis, N., Theodoridis, Y., Nanni, M., Longhi, L., Koumparos, A., Yasar, A. and Kureshi, I.
                “Visual Analytics for Characterizing Mobility Aspects of Urban Context.” Wenzhong Shi, Michael Goodchild, Michael Batty, Mei-Po Kwan, Anshu Zhang (Eds.) Urban Informatics<\/strong>. Springer, 2020.
                Pre-print:                 http:\/\/geoanalytics.net\/and\/papers\/VA-urban20.pdf<\/a><\/li>
              2. Andrienko, N., Andrienko, G. “Visual Analytics of Vessel Movement.”
                Alexander Artikis and Dimitris Zissis (Eds.) Maritime Informatics<\/strong>. Springer, 2020.
                Pre-print:                 http:\/\/geoanalytics.net\/and\/papers\/VA-vessels20.pdf<\/a><\/li>
              3. Andrienko, N., Andrienko, G., Fuchs, G., Slingsby, A., Turkay, C., Wrobel, S. Visual Analytics for Data Scientists<\/strong>. Springer, 2020.
                Published version:                 https:\/\/www.springer.com\/gp\/book\/9783030561451<\/a><\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

                Journal publications Mobility-based Big Data: Integration and Processing Tampakis, P., Doulkeridis, C., Pelekis, N., Theodoridis, Y. 2020. \u201cDistributed Subtrajectory Join on Massive Datasets.\u201d ACM Digital Library. Click here for the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":49,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"om_disable_all_campaigns":false},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/pages\/77"}],"collection":[{"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/comments?post=77"}],"version-history":[{"count":76,"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/pages\/77\/revisions"}],"predecessor-version":[{"id":1901,"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/pages\/77\/revisions\/1901"}],"up":[{"embeddable":true,"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/pages\/49"}],"wp:attachment":[{"href":"https:\/\/trackandknowproject.eu\/wp-json\/wp\/v2\/media?parent=77"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}