Using page classification and association rule mining for personalized recommendation in distance learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

With the rapid development of Internet, distance learning applications over Internet become more and more popular. This paper introduces a personalized learning system for web-based distance learning and focus on the web usage mining techniques aimed at personalized recommendation service. First, this paper presents a web page classification method, which uses attribute-oriented induction method according to related domain knowledge shown by a concept hierarchy tree. Second, the paper presents an algorithm of mining association rules with one-support using Freq- Set-Tree. Third, based on their current access patterns, page classes at the home site, page integration from other sites, and the rules discovered in mining, recommendation pages are made and presented for the students.

Original languageEnglish
Title of host publicationAdvances in Web-Based Learning - 1st International Conference, ICWL 2002, Proceedings
EditorsJoseph Fong, Chu Ting Cheung, Hong Va Leong, Qing Li
PublisherSpringer Verlag
Pages363-374
Number of pages12
ISBN (Electronic)3540440410, 9783540440413
DOIs
Publication statusPublished - 2002
Externally publishedYes
Event1st International Conference on Web-Based Learning, ICWL 2002 - Hong Kong, China
Duration: 17 Aug 200219 Aug 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2436
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Web-Based Learning, ICWL 2002
Country/TerritoryChina
CityHong Kong
Period17/08/0219/08/02

Fingerprint

Dive into the research topics of 'Using page classification and association rule mining for personalized recommendation in distance learning'. Together they form a unique fingerprint.

Cite this