Web usage mining using kuktem e-community application

Hasimah, Razak (2005) Web usage mining using kuktem e-community application. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

[img]
Preview
PDF
HASIMAH_RAZAK.PDF

Download (781kB)

Abstract

The continuous growth of the information on the Internet enables users to get the convenient and yet accurate tools to gain the information needed.However, the explosion of unlimited information difficult the users to get the information needed and administrator having difficulties to provide the information needed by users for particular website. This is because, the administrators do not know what the users surf when they visit any particular website. Considering the problems that are faced by users and administrators, a data mining application will be developed. The aims of the application are to determine the general patterns of site usage and to determine the user's interest based on the option provided by the site. With the existence of this application, it will improve the quality of a website. To develop this data mining application, visual.Basis is used with the Rapid Software Development Life Cycle methodology.Information collected by Web servers and kept in the server logs is the main source of data for analyzing user navigation patterns. Once logs have been preprocessed and sessions have been obtained, there are several kinds of access patterns mining that can be performed depending on the needs of the analyst. Some of the navigation patterns that will be produced are the most requested pages and the most downloaded files. Beside that, support and confidence for each user's access option will be counted to know the users interest and to predict whether the visitor of a website will be more or less. If support less than confidence, there will be more visitors of a website and viceversa. In this paper, Generalized Association Rule will be used in order to optimize to content of website.

Item Type: Undergraduates Project Papers
Uncontrolled Keywords: Data mining Internet computer network World wide web information retrieval system
Subjects: Q Science > QA Mathematics
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Shamsor Masra Othman
Date Deposited: 16 May 2013 04:22
Last Modified: 03 Mar 2015 08:02
URI: http://umpir.ump.edu.my/id/eprint/3690
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item