Standard
Harvard
Fragos, S, Stergioulas, L
& Xydeas, C 2003,
Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis. in V Palade, R Howlett & L Jain (eds),
Knowledge-Based Intelligent Information and Engineering Systems 7th International Conference, KES 2003, Oxford, UK, September 2003. Proceedings, Part II. vol. 2774, Lecture Notes in Computer Science, vol. 2774, Springer, Berlin, pp. 73-79.
https://doi.org/10.1007/978-3-540-45226-3_11APA
Fragos, S., Stergioulas, L.
, & Xydeas, C. (2003).
Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis. In V. Palade, R. Howlett, & L. Jain (Eds.),
Knowledge-Based Intelligent Information and Engineering Systems 7th International Conference, KES 2003, Oxford, UK, September 2003. Proceedings, Part II (Vol. 2774, pp. 73-79). (Lecture Notes in Computer Science; Vol. 2774). Springer.
https://doi.org/10.1007/978-3-540-45226-3_11Vancouver
Fragos S, Stergioulas L
, Xydeas C.
Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis. In Palade V, Howlett R, Jain L, editors, Knowledge-Based Intelligent Information and Engineering Systems 7th International Conference, KES 2003, Oxford, UK, September 2003. Proceedings, Part II. Vol. 2774. Berlin: Springer. 2003. p. 73-79. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-45226-3_11
Author
Bibtex
@inproceedings{090eeb0580cd4bac9d205090c5aa1190,
title = "Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis",
abstract = "The purpose of the work is to demonstrate the usefulness and applicability of audit trail data for modeling, classifying and predicting human user decision behavior using Independent Component Analysis. A hybrid behavior-modeling method, based on independent component analysis and sensitivity analysis, is proposed to directly classify decision behavior in terms of predetermined target measures. A comparison with alternative principal component analysis schemes demonstrates the advantages of the proposed method in terms of algorithmic speed, complexity, practical feasibility and data reduction capability. The capability of the system to provide intelligent support to executive decision making and internal control and to assist in several phases of the decision making process is highlighted.",
author = "Serafeim Fragos and Lampros Stergioulas and Costas Xydeas",
year = "2003",
doi = "10.1007/978-3-540-45226-3_11",
language = "English",
isbn = "978-3-540-40804-8",
volume = "2774",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "73--79",
editor = "Vasile Palade and Robert Howlett and Lakhmi Jain",
booktitle = "Knowledge-Based Intelligent Information and Engineering Systems 7th International Conference, KES 2003, Oxford, UK, September 2003. Proceedings, Part II",
}
RIS
TY - GEN
T1 - Classification of Decision-Behavior Patterns in Multivariate Computer Log Data Using Independent Component Analysis
AU - Fragos, Serafeim
AU - Stergioulas, Lampros
AU - Xydeas, Costas
PY - 2003
Y1 - 2003
N2 - The purpose of the work is to demonstrate the usefulness and applicability of audit trail data for modeling, classifying and predicting human user decision behavior using Independent Component Analysis. A hybrid behavior-modeling method, based on independent component analysis and sensitivity analysis, is proposed to directly classify decision behavior in terms of predetermined target measures. A comparison with alternative principal component analysis schemes demonstrates the advantages of the proposed method in terms of algorithmic speed, complexity, practical feasibility and data reduction capability. The capability of the system to provide intelligent support to executive decision making and internal control and to assist in several phases of the decision making process is highlighted.
AB - The purpose of the work is to demonstrate the usefulness and applicability of audit trail data for modeling, classifying and predicting human user decision behavior using Independent Component Analysis. A hybrid behavior-modeling method, based on independent component analysis and sensitivity analysis, is proposed to directly classify decision behavior in terms of predetermined target measures. A comparison with alternative principal component analysis schemes demonstrates the advantages of the proposed method in terms of algorithmic speed, complexity, practical feasibility and data reduction capability. The capability of the system to provide intelligent support to executive decision making and internal control and to assist in several phases of the decision making process is highlighted.
U2 - 10.1007/978-3-540-45226-3_11
DO - 10.1007/978-3-540-45226-3_11
M3 - Conference contribution/Paper
SN - 978-3-540-40804-8
VL - 2774
T3 - Lecture Notes in Computer Science
SP - 73
EP - 79
BT - Knowledge-Based Intelligent Information and Engineering Systems 7th International Conference, KES 2003, Oxford, UK, September 2003. Proceedings, Part II
A2 - Palade, Vasile
A2 - Howlett, Robert
A2 - Jain, Lakhmi
PB - Springer
CY - Berlin
ER -
