Predicting Users Behavior from the Analysis of Web Server logs Using Hash Map and PAFI Algorithm

Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

A Weblogs contains series of transactions updated frequently, while users accessing the websites. It comprises of various entries like IP address, status code and number of bytes transferred, categories and time stamp. The user interest can be classified based on categories and attributes and it is helpful in identifying user behavior. The log query parser is to convert unstructured log to structured log based on user interest. The weblog data can be classified as successful and unsuccessful data. The aim of the research is to classify the data of success response and analyze the user navigation. The process of identifying user behavior consisting of data collection, query parser, pre-processing and pattern analysis that will help us to analyze and predict the user behavior in short time. This research work explores to analyze the user prediction, based on the user preference present in various levels that is captured from weblogs.

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Keywords

User navigation, web mining, user behavior, traversal pattern, prediction accuracy, Data Mining.