Research aligned analysis on web access behavioral pattern mining for user identification

Title

Research aligned analysis on web access behavioral pattern mining for user identification

Creator

Gokulapriya R.; Ganesh Kumar R.

Description

Human activity understanding includes activity recognition and activity pattern discovery. Monitoring human activity and finding abnormality in their activities used by many field like medical applications, security systems etc. Basically it helps and support in decision making systems. Mining user activity from web logs can helps in finding hidden information about the user access pattern which reveals the web access behaviour of the users. Clustering and Classification techniques are used for web user identification. Clustering is the task of grouping similar patterns for web user identification. Classification is the process of classifying web patterns for user identification. In this paper we have implemented the existing works and discussed the results here to find the limitations. In existing methods, many data mining techniques were introduced for web user behaviour identification. But, the user identification accuracy was not improved and time consumption was not reduced. Our objective is to study the existing work and explore the possibility to improve the identification accuracy and reduce the time consumption using machine learning and deep learning techniques. BEIESP.

Source

International Journal of Engineering and Advanced Technology, Vol-8, No. 6, pp. 5062-5067.

Date

2019-01-01

Publisher

Blue Eyes Intelligence Engineering and Sciences Publication

Subject

Data mining; Human activity understanding; User Idenifiction; Web patterns; Web usage mining; Web user behavior

Coverage

Gokulapriya R., Computer Science and Engineering, CHRIST (Deemed to be University), India; Ganesh Kumar R., Computer Science and Engineering, CHRIST (Deemed to be University), India

Rights

All Open Access; Gold Open Access

Relation

ISSN: 22498958

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.35940/ijeat.F9552.088619

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85072060134&doi=10.35940%2fijeat.F9552.088619&partnerID=40&md5=1854aef2ea25ec163eadb96aca3307c4