S. Safayet-alam and R. Jianu, Analyzing eye-tracking information in visualization and data space: from where on the screen to what on the screen, IEEE Transactions on Visualization and Computer Graphics, vol.23, pp.1492-1505, 2017.

R. Amar and J. Stasko, A knowledge task-based framework for design and evaluation of information visualizations, IEEE Symposium on Information Visualization, pp.143-150, 2004.

G. Andrienko, N. Andrienko, P. Bak, D. Keim, and S. Wrobel, Visual analytics of movement, pp.73-101, 2013.

G. Andrienko, N. Andrienko, G. Budziak, J. Dykes, G. Fuchs et al., Visual analysis of pressure in football, Journal Data Mining and Knowledge Discovery, vol.31, pp.1793-1839, 2017.

G. Andrienko, N. Andrienko, M. Burch, and D. Weiskopf, Visual analytics methodology for eye movement studies, IEEE Transactions on Visualization and Computer Graphics, vol.18, pp.2889-2898, 2012.

G. Andrienko, N. Andrienko, G. Fuchs, and J. Garcia, Clustering trajectories by relevant parts for air traffic analysis, IEEE Transactions on Visualization and Computer Graphics, vol.24, pp.34-44, 2018.

N. Andrienko and G. Andrienko, , 2019.

N. Andrienko, G. Andrienko, J. Garcia, and D. Scarlatti, analysis of flight variability: a systematic approach, IEEE Transactions on Visualization and Computer Graphics, vol.25, pp.54-64, 2019.

R. Bednarik, Potentials of eye-movement tracking in adaptive systems, Proceedings of the 4th Workshop on Empirical Evaluation of Adaptive Systems, pp.1-8, 2005.

J. Bertin, Sémiologie graphique, 1967.

T. Blascheck, M. John, K. Kurzhals, S. Koch, and T. Ertl, VA 2 : a visual analytics approach for evaluating visual analytics applications, IEEE Transactions on Visualization and Computer Graphics, vol.22, pp.61-70, 2016.

T. Blascheck, K. Kurzhals, M. Raschke, M. Burch, D. Weiskopf et al., Visualization of eye tracking data: a taxonomy and survey, Computer Graphics Forum, vol.36, pp.260-284, 2017.

J. Blattgerste, P. Renner, and T. Pfeiffer, Advantages of eye-gaze over head-gaze-based selection in virtual and augmented reality under varying field of views, COGAIN '18 Proceedings of the Workshop on Communication by Gaze Interaction, vol.1, pp.1-1, 2018.

S. Blog, Eye tracking technology -user profiling and privacy concerns, 2017.

M. Borys and M. Plechawska-wójcik, Eye-tracking metrics in perception and visual attention research, European Journal of Medical Technologies, pp.11-23, 2017.

M. Brehmer and T. Munzner, A multi-level typology of abstract visualization tasks, IEEE Transactions on Visualization and Computer Graphics, vol.19, pp.2376-2385, 2013.

N. Sylvain-castagnos, P. Jones, and . Pu, Eye-tracking product recommenders' usage, Proceedings of the ACM Conference on Recommender systems, pp.29-36, 2010.

S. Castagnos and P. Pu, Consumer decision patterns through eye gaze analysis, Proceedings of the Workshop on Eye Gaze in Intelligent Human Machine Interaction, pp.78-85, 2010.

D. Ceneda, T. Gschwandtner, T. May, S. Miksch, H. Schulz et al., Characterizing guidance in visual analytics, IEEE Transactions on Visualization and Computer Graphics, vol.23, pp.111-120, 2017.

L. Chen and P. Pu, Users' eye gaze pattern in organization-based recommender interfaces, Proceedings of the 16th International Conference on Intelligent User Interfaces, pp.311-314, 2011.

L. Chuang, A. Duchowski, P. Qvarfordt, and D. Weiskopf, Ubiquitous gaze sensing and interaction (Dagstuhl seminar 18252), Dagstuhl Reports, vol.8, pp.77-148, 2019.

C. Collins, N. Andrienko, T. Schreck, J. Yang, J. Choo et al., Guidance in the human-machine analytics process, Visual Informatics, vol.2, pp.166-180, 2018.

A. Neven, B. H. Elsayed, K. Thomas, J. Marriott, R. T. Piantadosi et al., Situated analytics: demonstrating immersive analytical tools with augmented reality, Journal of Visual Languages & Computing, vol.36, pp.13-23, 2016.

A. Endert, W. Ribarsky, C. Turkay, B. L. William-wong, I. T. Nabney et al., The state of the art in integrating machine learning into visual analytics, Computer Graphics Forum, vol.36, pp.458-486, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01714743

P. Federico, M. Wagner, A. Rind, A. Amor-amorós, S. Miksch et al., The role of explicit knowledge: a conceptual model of knowledge-assisted visual analytics, Proc. IEEE Conference on Visual Analytics Science and Technology (VAST), 2017.

A. Felfernig, M. Jeran, G. Ninaus, F. Reinfrank, and S. Reiterer, Toward the next generation of recommender systems: applications and research challenges, In Multimedia Services in Intelligent Environments, pp.81-98, 2013.

M. Frutos, -. , and B. Garcia-zapirain, Assessing visual attention using eye tracking sensors in intelligent cognitive therapies based on serious games, Sensors, vol.15, pp.11092-11117, 2015.

F. Göbel, P. Kiefer, I. Giannopoulos, A. Duchowski, and M. Raubal, Improving map reading with gaze-adaptive legends, Proceedings of the ACM Symposium on Eye Tracking Research & Applications. ACM, vol.29, p.9, 2018.

F. Haag, T. Blascheck, B. Schmitz, and M. Raschke, Berührpunkte mit der visualisierung, Multi-Touch -Interaktion Durch Beruhrung, Thomas Schlegel, pp.339-367, 2013.

J. Han, M. Kamber, and J. Pei, Data mining: concepts and techniques, 2011.

C. Hurter, N. H. Riche, S. M. Drucker, M. Cordeil, R. Alligier et al., Fiberclay: sculpting three dimensional trajectories to reveal structural insights, IEEE Transactions on Visualization and Computer Graphics, vol.25, pp.704-714, 2019.
URL : https://hal.archives-ouvertes.fr/hal-01857930

R. Jianu and S. Safayet-alam, A data model and task space for data of interest (DOI) eye-tracking analyses, IEEE Transactions on Visualization and Computer Graphics, vol.24, pp.1232-1245, 2018.

J. Jung, Y. Matsuba, R. Mallipeddi, H. Funaya, K. Ikeda et al., Evolutionary programming based recommendation system for online shopping, Signal and Information Processing Association Annual Summit and Conference (APSIPA), pp.1-4, 2013.

M. Just and P. Carpenter, A theory of reading: from eye fixations to comprehension, Psychological Review, vol.87, pp.329-354, 1980.

D. Keim, F. Mansmann, J. Schneidewind, J. Thomas, and H. Ziegler, Visual analytics: scope and challenges, Visual Data Mining, pp.76-90, 2008.

D. A. Keim, J. Kohlhammer, G. Ellis, and F. Mansmann, Mastering the information age -solving problems with visual analytics, 2010.

P. Kiefer, I. Giannopoulos, and M. Raubal, Using eye movements to recognize activities on cartographic maps, Proceedings of the 21st ACM SIGSPA-TIAL 2013, pp.488-491, 2013.

K. Kurzhals, B. Fisher, M. Burch, and D. Weiskopf, Evaluating visual analytics with eye tracking, Proceedings of the BELIV Workshop: Beyond Time and Errors -Novel Evaluation Methods for Visualization, pp.61-69, 2014.

D. Lagun, C. Manzanares, S. M. Zola, E. A. Buffalo, and E. Agichtein, Detecting cognitive impairment by eye movement analysis using automatic classification algorithms, Journal of Neuroscience Methods, vol.201, pp.196-203, 2011.

B. Law, Privacy issues in virtual reality: eye tracking technology, 2017.

D. Liebling and S. Preibusch, Privacy considerations for a pervasive eye tracking world, Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp.1169-1177, 2014.

N. Marianos, Foveated rendering algorithms using eye-tracking technology in virtual reality, 2018.

T. Munzner, Visualization analysis and design, 2014.

M. Okoe, S. Safayet-alam, and R. Jianu, A gaze-enabled graph visualization to improve graph reading tasks, Computer Graphics Forum, vol.33, 2014.

O. David, D. Sullivan, and . Unwin, Geographic information analysis, 2014.

W. Pike, J. Stasko, R. Chang, and T. Connell, The science of interaction, Information Visualization, vol.8, pp.263-274, 2009.

B. Preim and R. Dachselt, Interaktive systeme: band 1: grundlagen, graphical user interfaces, informationsvisualisierung, 2010.

A. M. Razip, A. Malik, S. Afzal, M. Potrawski, R. Maciejewski et al., A mobile visual analytics approach for law enforcement situation awareness, Proceedings of the IEEE Pacific Visualization Symposium, pp.169-176, 2014.

P. Renner and T. Pfeiffer, Attention guiding techniques using peripheral vision and eye tracking for feedback in augmented-reality-based assistance systems, Proceedings of the Symposium on 3D User Interfaces (3DUI, pp.186-194, 2017.

D. Sacha, A. Stoffel, F. Stoffel, G. Bum-chul-kwon, D. Ellis et al., Knowledge generation model for visual analytics, IEEE Transactions on Visualization and Computer Graphics, vol.20, pp.1604-1613, 2014.

L. Shao, N. Silva, E. Eggeling, and T. Schreck, Visual exploration of large scatter plot matrices by pattern recommendation based on eye tracking, Proceedings of the 2017 ACM Workshop on Exploratory Search and Interactive Data Analytics, pp.9-16, 2017.

B. Shneiderman, The eyes have it: a task by data type taxonomy for information visualizations, Proceedings of the IEEE Symposium on Visual Languages, pp.336-343, 1996.

N. Silva, T. Schreck, E. Veas, V. Sabol, E. Eggeling et al., Leveraging eye-gaze and time-series features to predict user interests and build a recommendation model for visual analysis, Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, p.13, 2018.

N. Silva, V. Settgast, E. Eggeling, T. Ullrich, T. Schreck et al., Increasing fault tolerance in operational centres using human sensing technologies: approach and initial results, p.25, 2015.

N. Silva, L. Shao, T. Schreck, E. Eggeling, and D. W. Fellner, Sense.me -open source framework for the exploration and visualization of eye tracking data, Proceedings of the 2016 IEEE Conference on Information Visualization, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01827519

N. Silva, L. Shao, T. Schreck, E. Eggeling, and D. W. Fellner, Visual exploration of hierarchical data using degree-of-interest controlled by eyetracking, Proceedings of the 9th Forum Media Technology 2016 and 2nd All Around Audio Symposium, pp.82-89, 2016.

H. Song and N. Moon, A preference based recommendation system design through eye-tracking and social behavior analysis, Advances in Computer Science and Ubiquitous Computing, pp.1014-1019, 2017.

J. Stanley, The privacy-invading potential of eye tracking technology, 2013.

B. Steichen, G. Carenini, and C. Conati, User-adaptive information visualization: using eye gaze data to infer visualization tasks and user cognitive abilities, Proceedings of the International Conference on IUIs, pp.317-328, 2013.

. Tableau, Tableau software, 2019.

Y. Terao, H. Fukuda, and O. Hikosaka, What do eye movements tell us about patients with neurological disorders?: -an introduction to saccade recording in the clinical setting, Proceedings of the Japan Academy, Series B, Physical and Biological Sciences, vol.93, issue.10, p.29225306, 2017.

J. J. Thomas and K. A. Cook, Illuminating the path: the research and development agenda for visual analytics, 2005.

W. Kwan-chun, J. Ting, M. D. Velazquez, and . Cusimano, Eye movement measurement in diagnostic assessment of disorders of consciousness, Frontiers in Neurology, vol.5, p.25120529, 2014.

S. Tatiana-von-landesberger, S. Fiebig, A. Bremm, D. Kuijper, and . Fellner, Interaction taxonomy for tracking of user actions in visual analytics applications, Handbook of Human Centric Visualization, Weidong Huang, pp.653-670, 2014.

S. Xu, H. Jiang, and F. Lau, Personalized online document, image and video recommendation via commodity eye-tracking, Proceedings of the 2008 ACM conference on Recommender systems, pp.83-90, 2008.

J. S. Yi, Y. Kang, J. Stasko, and J. Jacko, Toward a deeper understanding of the role of interaction in information visualization, IEEE Transactions on Visualization and Computer Graphics, vol.13, pp.1224-1231, 2007.

Q. Zhao, S. Chang, M. Harper, and J. A. Konstan, Gaze prediction for recommender systems, Proceedings of the 10th ACM Conference on Recommender Systems, pp.131-138, 2016.