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001-es BibID:BIBFORM077946
035-os BibID:(cikkazonosító)e3003
Első szerző:Gere Attila
Cím:Spectral clustering in eye-movement researches / Attila Gere, Sándor Kovács, László Sipos
Dátum:2018
ISSN:0886-9383 1099-128X
Megjegyzések:Eye tracking is a widely used technology to capture the eye movements of participants completing different tasks. Several eye-tracking parameters are measured, which later can be used to characterize the gazing pattern of the individuals. Clustering based on the path walked on by the participants may enable the researchers to create clusters based on the unconscious personality and thinking style. Common clustering methods generally are unable to handle path data; hence, new dynamic variables are needed. Spectral clustering can handle these types of data well. Spectral clustering handles clustering as a graph partitioning problem without making specific assumptions on the form of the clusters and uses eigenvectors of matrices derived from the data. This way, data are mapped to a low-dimensional space, which can be easily clustered. Different food choice tasks were presented, and each of the 149 participants had to choose 1 product of the presented 4 and later from 8 alternatives. A new measure was introduced based on all 3 consecutive points from the fixations, and the areas of the triangles formed by these 3 points were computed. The new eye-movement index captures the temporal variation and also considers the orientation of the fixation points. Spectral clustering resulted 5 balanced clusters defined by Dunn, Silhouette, and C-indices. Results were compared to the most widely applied hierarchical and centroid-based clustering (k-means) methods. Spectral clustering achieved the best results in clustering indices and cluster sizes proved to be more balanced; hence, it outperforms the commonly used applied hierarchical and k-means.
Tárgyszavak:Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Journal of Chemometrics. - 32 : 4 (2018), p. 1-10. -
További szerzők:Kovács Sándor (1978-) (matematika tanár) Sipos László (agrár)
Pályázati támogatás:ÚNKP?17?4
egyéb
OTKA K119269
OTKA
VEKOP?2.3.3?15?2017?00022
VEKOP
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2.

001-es BibID:BIBFORM077945
035-os BibID:(cikkazonosító)e3011
Első szerző:Sipos László (agrár)
Cím:A novel ranking distance measure combining Cayley and Spearman footrule metrics / László Sipos, Attila Gere, József Popp, Sándor Kovács
Dátum:2018
ISSN:0886-9383
Megjegyzések:Defining the appropriate ranking distance measures among rankings is a classicarea of study. The goal of our work is to identify a combination of methodologies, which is proven to be capable for the determination of a proper rankingsystem. In our study, we used 3 well-established metrics: Kendall tau,Spearman footrule, and Cayley distance and a novel metric created by thecombination of Cayley and Spearman footrule metrics. The results of the newlyintroduced metric depend on how fast we can trade a permutation of items tothe reference permutation according to the Spearman footrule. On the otherhand, the distance also depends on the number of cycles and the inversionsin the cycle. Two case studies - chemometric data of phytonutrients of tomatovarieties and sensometric data of orange juices - were used to test theperformance of the studied ranking distance metrics. The properties ofthe new metric were compared to the traditional metrics regarding the normality of their distributions, significant number of differences between the ratingobjects, and the quality of the rankings. Results were validated by leave-one-out cross-validation and significant differences by Wilcoxon matched pairs test.
Tárgyszavak:Természettudományok Matematika- és számítástudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Journal of Chemometrics. - 32 : 4 (2018), p. 1-12. -
További szerzők:Gere Attila Popp József (1955-) (közgazdász) Kovács Sándor (1978-) (matematika tanár)
Pályázati támogatás:ÚNKP?17?4
egyéb
OTKA K119269
OTKA
VEKOP 2.3.3?15?2017?00022
VEKOP
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
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