Semantic Web recommender system based personalization service for user XQuery pattern

Jin Hong Kim, Eun Seok Lee

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

6 Scopus citations

Abstract

Semantic Web Recommender Systems is more complex than traditional Recommender System in that it raises many new issues such as user profiling, navigation pattern. Semantic Web based Recommender Service aims at combining the two fast-developing research areas Semantic Web and User XQuery. Nevertheless, as the number of web pages increases rapidity, the problem of the information overload becomes increasingly severe when browsing and searching the World Wide Web. To solve this problem, personalization becomes a popular solution to customize the World Wide Web environment towards a user's preference. The idea is to improve by analyze of user query pattern for recommender service in the Web and to make use for building up the Semantic Web. In this paper, we present a user XQuery method for personalization Service using Semantic Web.

Original languageEnglish
Title of host publicationInternet and Network Economics - First International Workshop, WINE 2005, Proceedings
Pages848-857
Number of pages10
DOIs
StatePublished - 2005
Event1st International Workshop on Internet and Network Economics, WINE 2005 - Hong Kong, China
Duration: 15 Dec 200517 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3828 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Internet and Network Economics, WINE 2005
Country/TerritoryChina
CityHong Kong
Period15/12/0517/12/05

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