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Mining same-taste users with common preference patterns for ubiquitous exhibition navigation

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

Abstract

In a ubiquitous exhibition, an intelligent navigation service that can provide booths' information, recommend interesting booths and plan touring path is required for both visitors and vendors. The preference mining module is the kernel. This paper proposes a group-based user preference pattern mining method, which can be implemented as a preference mining module in this service. When the visiting traces that imply the preference of users are recorded, the method discovers user preference patterns with high representativeness and high discrimination from the historical visiting logs. According to the discovered model, collaborative recommendation can be accomplished, and then the intelligent navigation service can plan personalized touring path based on the recommendation lists. For demonstrating the performance of the proposed method, we engage some experiments, and then indicate the characteristics of the proposed method.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings
Pages416-425
Number of pages10
EditionPART 3
DOIs
StatePublished - 2012
Event4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012 - Kaohsiung, Taiwan
Duration: 19 Mar 201221 Mar 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume7198 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012
Country/TerritoryTaiwan
CityKaohsiung
Period19/03/1221/03/12

Keywords

  • Ubiquitous exhibition
  • clustering
  • collaborative recommendation
  • data mining
  • user preference pattern

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