A Novel Approach for User Navigation Pattern Discovery and Analysis for Web Usage Mining

Abstract

Websites on the internet are useful source of information in our day-to-day activity. Web Usage Mining (WUM) is one of the major applications of data mining, artificial intelligence and so on to the web data to predict the user's visiting behaviours and obtains their interests by analyzing the patterns.WUM has turned out to be one of the considerable areas of research in the field of computer and information science. Weblog is one of the major sources which contain all the information regarding the users visited links, browsing patterns, time spent on a page or link and this information can be used in several applications like adaptive web sites, personalized services, customer profiling, prefetching, creating attractive web sites etc. WUM consists of preprocessing, pattern discovery and pattern analysis. Log data is typically noisy and unclear, so preprocessing is an essential process for effective mining process. In the preprocessing phase, the data cleaning process includes removal of records of graphics, videos, format information, records with the failed HTTP status code and robots cleaning. In the second phase, the user behaviour is organized into a set of clusters using Weighted Fuzzy-Possibilistic C-Means (WFPCM), which consists of "similar" data items based on the user behaviour and navigation patterns for the use of pattern discovery. In the third phase, classification of the user behaviour is carried out for the purpose of analyzing the user behaviour using Adaptive Neuro-Fuzzy Inference System with Subtractive Algorithm (ANFIS-SA). The performance of the proposed work is evaluated based on accuracy, execution time and convergence behaviour using anonymous microsoft web dataset.

User behaviour pattern for online learning system: UiTM iLearn portal case

“…The user navigation behaviour based on preferences can be predicted from the result of web usage mining. Web usage mining is one of the active research areas and extensive research work has been carried out in the recent years [10]. There are number of techniques have been proposed by various author including acquisition of web log, preprocessing, pattern discovery and pattern analysis.…”

A Review Analysis of Preprocessing Techniques in Web usage Mining

“…Among them data preprocessing is essential stage which can done by data collection, data cleaning, user identification, session identification, path completion, transaction identification and formatting [5]. Because of log file contains bulk of data, preprocessing of log file reformats the entries of a log file into a form that can be used directly by subsequent steps of the log analyzer [7].…”

“…Vellingiri J. et al [7]provided three phases of web usage mining for user navigation discovery including preprocessing phase, Identify user's behavior and classifications of user behaviors. In the preprocessing phase, the data cleaning process includes removal of graphics, video, status code and robots cleaning.…”

Chi-square based hierarchical agglomerative clustering for web sessionization

“…The different web server log files has been discussed by Vellingiri et al (2015). Web log is stored in plain text format (ASCII) and that is a part of the operating system rather than a part of web application.…”

“…Journal of the National Science Foundation of Sri Lanka 44 (2) The user's click record is the key to investigate user trends and behaviour on a specific website (Wang & Lee, 2011;Vellingiri et al, 2015). The analysis of user click streams is useful in many ways (Oliner et al, 2012) such as website management (Vaarandi, 2003), website administration, fraud detection, web personalisation, information retrieval systems (Sote & Pande, 2015) and recommended systems (Hussain et al, 2010b).…”