Performance Analysis of User Behavior Pattern Mining Using Web Log Database for User Identification

Title

Performance Analysis of User Behavior Pattern Mining Using Web Log Database for User Identification

Creator

Gokulapriya R.; Ganesh Kumar R.

Description

User behavior analytics is a progressive research domain. Understanding the users behavior patterns and identifying their behavior patterns will provide solutions to many issues like identity theft and user authentication. So many research works are done in analyzing the frequent access patterns of the users by pre-processing access logs and applying various algorithms to understand the frequent access behavior of the user. From the literature, it founds that the frequent user access pattern identification needs improvement on prediction accuracy and the minimal false positives. To accomplish these, three different approaches were proposed to overcome the existing issues and intended to reduce false positives and improve the frequent pattern mining accuracy based on web access logs. Proposed methods were found to be good while compared with the existing works. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-627 LNNS, pp. 347-356.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Frequent pattern identification; Mutual pre-processing; User access pattern; Web access mining

Coverage

Gokulapriya R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST(Deemed to be University), Karnataka, Bangalore, India; Ganesh Kumar R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST(Deemed to be University), Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981199857-7

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-9858-4_29

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85161435101&doi=10.1007%2f978-981-19-9858-4_29&partnerID=40&md5=4efd0e618b153977ba60a65fc76a7b6c