{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T12:37:55Z","timestamp":1763642275508,"version":"3.37.3"},"reference-count":35,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","funder":[{"name":"Nature science foundation of Jiangsu Province","award":["No. BK20150626"],"award-info":[{"award-number":["No. BK20150626"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71471037","71271053"],"award-info":[{"award-number":["71471037","71271053"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012154","name":"Scientific Innovation Research of College Graduates in Jiangsu Province","doi-asserted-by":"crossref","award":["No. KYLX_0104"],"award-info":[{"award-number":["No. KYLX_0104"]}],"id":[{"id":"10.13039\/501100012154","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2018,5]]},"abstract":"<jats:p> A new method based on eye-tracking data \u2014 visual momentum (VM) \u2014 was introduced to quantitatively evaluate a dynamic interactive visualization interface. We extracted the dimensionless factors from the raw eye-tracking data, including the fixation time factor [Formula: see text], the saccade amplitude factor D and the fixation number factor [Formula: see text]. A predictive regression model of VM was deduced by eye movement factors and the performance response time (RT). In Experiment 1, the experimental visualization materials were designed with six effectiveness levels according to design techniques proposed by Woods to improve VM (total replacement, fixed format data replacement, long shot, perceptual landmark and spatial representation) and were tested in six parallel subject groups. The coefficients of the regression model were calculated from the data of 42 valid subjects in Experiment 1. The mean VM of each group exhibited an increasing trend with an increase in design techniques. The data of the performance and eye tracking among the combined high VM group, middle VM group and low VM group indicated significant differences. The data analysis indicates that the results were consistent with the previous qualitative research of VM. We tested and verified this regression model in Experiment 2 with another dynamic interactive visualization. The results indicated that the VM calculated by the regression model was significantly correlated with the performance data. Therefore, the virtual parameter VM can be a quantitative indicator for evaluating dynamic visualization. It could be a useful evaluation method for the dynamic visualization in general working environments. <\/jats:p>","DOI":"10.1142\/s0218001418500167","type":"journal-article","created":{"date-parts":[[2017,10,9]],"date-time":"2017-10-09T22:02:28Z","timestamp":1507586548000},"page":"1850016","source":"Crossref","is-referenced-by-count":10,"title":["An Evaluation Method of Visualization Using Visual Momentum Based on Eye-Tracking Data"],"prefix":"10.1142","volume":"32","author":[{"given":"Xiaozhou","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Southeast University, Nanjing 211189, P. R. China"}]},{"given":"Chengqi","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southeast University, Nanjing 211189, P. R. China"}]},{"given":"Lei","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Southeast University, Nanjing 211189, P. R. 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