Classification of Web Logs Using Hybrid Functional Link Artificial Neural Networks

被引：0

作者：

Behera, Ajit Kumar ^{[1
]}

Dash, Ch. Sanjeev Kumar ^{[2
]}

Dehuri, Satchidananda ^{[3
]}

机构：

[1] Silicon Inst Technol, Dept Comp Applicat, Silicon Hills, Bhubaneswar 751024, Orissa, India

[2] Silicon Inst Technol, Dept Comp Sci & Engn, Bhubaneswar 751024, Orissa, India

[3] Fakir Mohan Univ, Dept Informat & Commun Technol, Balasore 756019, Odisha, India

来源：

PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON FRONTIERS OF INTELLIGENT COMPUTING: THEORY AND APPLICATIONS (FICTA) 2014, VOL 1 | 2015年 / 327卷

关键词：

Differential evolution; Functional link artificial neural network; Classification; Web log;

D O I：

10.1007/978-3-319-11933-5_28

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Over the decades, researchers are striving to understand the web usage pattern of a user and are also extremely important for the owners of a website. In this paper, a hybrid analyzer is proposed to find out the browsing patterns of a user. Moreover, the pattern which is revealed from this surge of web access logs must be useful, motivating, and logical. A smooth functional link artificial neural network has been used to classify the web pages based on access time and region. The accuracy and smoothness of the network is taken birth by suitably tuning the parameters of functional link neural network using differential evolution. In specific, the differential evolution is used to fine tune the weight vector of this hybrid network and some trigonometric functions are used in functional expansion unit. The simulation result shows that the proposed learning mechanism is evidently producing better classification accuracy.

引用

页码：255 / 263

页数：9

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