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Author: Mikhail Petrovskiy

Affiliation: Faculty of Computational Mathematics and Cybernetics, Moscow State University, Russian Federation

Keyword(s): User behavior modeling, Data mining, Database access logs, Probabilistic models.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Communication and Software Technologies and Architectures ; Computational Intelligence ; Data Engineering ; Data Warehouses and Data Mining ; e-Business ; Enterprise Information Systems ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems ; User Modeling ; Web Information Systems and Technologies ; Web Interfaces and Applications

Abstract: The problem of user behavior modeling arises in many fields of computer science and software engineering. In this paper we investigate a data mining approach for learning probabilistic user behavior models from the database usage logs. We propose a procedure for translating database traces into representation suitable for applying data mining methods. However, most existing data mining methods rely on the order of actions and ignore time intervals between actions. To avoid this problem we propose novel method based on combination of decision tree classification algorithm and empirical time-dependent feature map, motivated by potential functions theory. The performance of the proposed method was experimentally evaluated on real-world data. The comparison with existing state-of-the-art data mining methods has confirmed outstanding performance of our method in predictive user behavior modeling and has demonstrated competitive results in anomaly detection.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Petrovskiy, M. (2006). A DATA MINING APPROACH TO LEARNING PROBABILISTIC USER BEHAVIOR MODELS FROM DATABASE ACCESS LOG. In Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT; ISBN 978-972-8865-69-6; ISSN 2184-2833, SciTePress, pages 73-78. DOI: 10.5220/0001321200730078

@conference{icsoft06,
author={Mikhail Petrovskiy.},
title={A DATA MINING APPROACH TO LEARNING PROBABILISTIC USER BEHAVIOR MODELS FROM DATABASE ACCESS LOG},
booktitle={Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT},
year={2006},
pages={73-78},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001321200730078},
isbn={978-972-8865-69-6},
issn={2184-2833},
}

TY - CONF

JO - Proceedings of the First International Conference on Software and Data Technologies - Volume 2: ICSOFT
TI - A DATA MINING APPROACH TO LEARNING PROBABILISTIC USER BEHAVIOR MODELS FROM DATABASE ACCESS LOG
SN - 978-972-8865-69-6
IS - 2184-2833
AU - Petrovskiy, M.
PY - 2006
SP - 73
EP - 78
DO - 10.5220/0001321200730078
PB - SciTePress