Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Neural Computing and Applications
Erschienen in: Neural Computing and Applications 5/2018

13.09.2016 | Original Article

Tabu search-based classification for eye-movement behavioral decisions

verfasst von: Peng-Yeng Yin, Rong-Fuh Day, Yu-Chi Wang

Erschienen in: Neural Computing and Applications | Ausgabe 5/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Adaptive human–computer interfaces (HCIs) are fundamental to designing adaptive websites and adaptive decision support systems. Integrating these intelligent systems with modern eye trackers provides more effective ways to exploit eye fixation data and offers improved services to users. We develop an exemplar-based classifier using the tabu search algorithm to predict which decision strategy may underlie an empirical search behavior. Our algorithm reduces the size of decision concept representations to find the best exemplars for each concept. Experimental results show that our classifier is highly accurate in classifying the sequence of empirical eye fixations, demonstrating the promise of integrating adaptive HCIs with modern eye trackers.
Vorheriger Artikel Exploring a narrative-based framework for historical exhibits combining JanusVR with photometric stereo
Nächster Artikel Development of adaptive p-step RBF network model with recursive orthogonal least squares training

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Aha DW, Kibler D, Albert MK (1991) Instance-based learning algorithms. Mach Learn 6(1):37–66
2.
Bettman JR, Johnson EJ, Payne JW (1990) A componential analysis of cognitive effort in choice. Organ Behav Hum Decis Process 45:111–139CrossRef
3.
Brandt SA, Stark LW (1997) Spontaneous eye movements during visual imagery reflect the content of the visual scene. J Cogn Neurosci 9(1):27–38CrossRef
4.
Brusilovsky P (2001) Adaptive hypermedia. User Model User Adapt Interact 11(1–2):87–110CrossRefMATH
5.
Chen Q (2001) Human computer interaction: issues and challenges. IGI Global, HersheyCrossRef
6.
Cover TM, Hart PE (1967) Nearest neighbor pattern classification. IEEE Trans Inf Theory 13(1):21–27CrossRefMATH
7.
Day R-F (2010) Examining the validity of the Needleman–Wunsch algorithm in identifying decision strategy with eye-movement data. Decis Support Syst 49(4):396–403CrossRef
8.
Dix A (2009) Human–computer interaction. Springer, Berlin
9.
Dorigo M, Gambardella LM (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53–66CrossRef
10.
11.
12.
13.
Glover F, Hanafi S (2010) Metaheuristic search with inequalities and target objectives for mixed binary optimization part i: exploiting proximity. Int J Appl Metaheuristic Comput 1(1):1–15CrossRef
14.
Glover F, Hanafi S (2010) Metaheuristic search with inequalities and target objectives for mixed binary optimization—part ii: exploiting reaction and resistance. Int J Appl Metaheuristic Comput 1(2):1–17CrossRef
15.
Glover F, Laguna M, Marti R (2000) Fundamentals of scatter search and path relinking. Control Cybern 29(3):653–684MathSciNetMATH
16.
Hair JF, Anderson RE, Tatham RL, Black WC (1998) Multivariate data analysis, 5th edn. Prentice-Hall, London
17.
Hegarty M, Mayer RE, Green CE (1992) Comprehension of arithmetic word problems: evidence from students’ eye fixations. J Educ Psychol 84(1):76–84CrossRef
18.
Holland JH (1975) Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press, Ann ArborMATH
19.
Just MA, Carpenter PA (1976) Eye fixations and cognitive processes. Cogn Psychol 8:441–480CrossRef
20.
Kirkpatrick S, Gelatt C Jr., Vecchi M (1983) Optimization by simulated annealing. Science 220(4598):671–680
21.
Laeng B, Teodorescu D-S (2002) Eye scanpaths during visual imagery reenact those of perception of the same visual scene. Cogn Sci 26:207–231CrossRef
22.
Laguna M, Marti R (2003) Scatter search: methodology and implementations in C. Kluwer Academic Publishers, Boston
23.
Levenshtein VI (1966) Binary codes capable of correcting deletions, insertions, and reversals. Sov Phys Dokl 10:707–710MathSciNetMATH
24.
Lin C-C (2006) Optimal web site reorganization considering information overload and search depth. Eur J Oper Res 173(3):839–848CrossRefMATH
25.
Mantaras RLD, Armengol E (1998) Machine learning from examples: inductive and lazy methods. Data Knowl Eng 25(1–2):99–123CrossRefMATH
26.
Maquera G, Laguna M, Gandelman DA, Sant’Anna AP (2011) Scatter search applied to the vehicle routing problem with simultaneous delivery and pickup. Int J Appl Metaheuristic Comput 2(2):1–20CrossRef
27.
Medin DL, Smith EE (1984) Concepts and concept formation. Annu Rev Psychol 35:113–138CrossRef
28.
Payne JW, Bettman JR, Johnson EJ (1993) The adaptive decision maker. Cambridge University Press, New YorkCrossRef
29.
Perkowitz M, Etzioni O (2000) Towards adaptive web sites: conceptual framework and case study. Artif Intell 118(1):245–275CrossRefMATH
30.
31.
Pomplug M, Sichelschmidt L, Wagner K, Clermont T, Rickheit G, Ritter H (2001) Comparative visual search: a difference that makes a difference. Cogn Sci 25:3–36CrossRef
32.
Qahri Saremi H, Abedin B, Meimand Kermani A (2008) Website structure improvement: quadratic assignment problem approach and ant colony meta-heuristic technique. Appl Math Comput 195(1):285–298MathSciNetMATH
33.
Rayner K (1998) Eye movements in reading and information processing: 20 years of research. Psychol Bull 124(3):372–422CrossRef
34.
Russo JE (2010) Eye fixations as a process trace. In: Schulte-Mecklenbeck M, Kuehberger A, Ranyard R (eds) A handbook of process tracing methods for decision research: a critical review and user’s guide. Taylor & Francis, Hove
35.
Russo JE, Rosen LD (1975) An eye fixation analysis of multialternative choice. Mem Cogn 3(3):267–276CrossRef
36.
Smith EE, Medin DL (1981) Categories and concepts. Harvard University Pres, CambridgeCrossRef
37.
Todd P, Benbasat I (1991) An experimental investigation of the impact of computer based decision aids on decision making strategies. Inf Syst Res 2(2):87–115CrossRef
38.
Todd P, Benbasat I (1992) The use of information in decision making: an experimental investigation of the impact of computer-based decision aids. MIS Q 16(3):373–393CrossRef
39.
Todd P, Benbasat I (1994) The influence of decision aids on choice strategies: an experimental analysis of the role of cognitive effort. Organ Behav Hum Decis Process 60:36–74CrossRef
40.
Todd P, Benbasat I (2000) Inducing compensatory information processing through decision aids that facilitate effort reduction: an experimental assessment. J Behav Decis Mak 13(1):91–106CrossRef
41.
Vertegaal R (2003) Attentive user interfaces. Commun ACM 46(3):30–33CrossRef
42.
West JM, Haake AR, Rozanski EP, Karn KS (2006) Eyepatterns: software for identifying patterns and similarities across fixation sequences. In: Proceedings of the 2006 symposium on Eye tracking research & applications New York, pp 149–154
43.
Wilson DR, Martinez TR (2000) Reduction techniques for instance-based learning algorithms. Mach Learn 38(3):257–286CrossRefMATH
44.
Yin P-Y, Guo Y-M (2013) Optimization of multi-criteria website structure based on enhanced tabu search and web usage mining. Appl Math Comput 219(24):11082–11095
Metadaten
Titel
Tabu search-based classification for eye-movement behavioral decisions
verfasst von
Peng-Yeng Yin
Rong-Fuh Day
Yu-Chi Wang
Publikationsdatum
13.09.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 5/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2583-2

Weitere Artikel der Ausgabe 5/2018

Neural Computing and Applications 5/2018 Zur Ausgabe

Neural Computing in Next Generation Virtual Reality Technology

Scale invariant point feature (SIPF) for 3D point clouds and 3D multi-scale object detection

Neural Computing in Next Generation Virtual Reality Technology

Discriminative anisotropic propagation with heat source estimation for robust object tracking

Neural Computing in Next Generation Virtual Reality Technology

Reality of virtual damage identification based on neural networks and vibration analysis of a damaged bridge under a moving vehicle

Neural Computing in Next Generation Virtual Reality Technology

Gamified learning through unity 3D in visualizing environments

Neural Computing in Next Generation Virtual Reality Technology

Quality assessment for virtual reality technology based on real scene

Neural Computing in Next Generation Virtual Reality Technology

Virtual reality of recognition technologies of the improved contour coding image based on level set and neural network models

Premium Partner

    Bildnachweise