Context-aware recommender system for location-based advertising

Hyunchul Ahn, Kyoung Jae Kim

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

2 Scopus citations

Abstract

Demand for context-aware systems continues to grow due to the diffusion of mobile devices. This trend may represent good market opportunities for mobile service industries. Thus, context-aware or location-based advertising (LBA) has been an interesting marketing tool for many companies. However, some studies reported that the performance of context-aware marketing or advertising has been quite disappointing. In this study, we propose a novel context-aware recommender system for LBA. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices - location, time and the user's needs type. In particular, we employ a classification rule to understand user's needs type using a decision tree algorithm. We empirically validated the effectiveness of the proposed model by using a real-world dataset. Experimental results show that our model makes more accurate and satisfactory advertisements than comparative systems.

Original languageEnglish
Title of host publicationMaterials, Mechatronics and Automation
PublisherTrans Tech Publications Ltd
Pages2091-2096
Number of pages6
ISBN (Print)9783037850176
DOIs
StatePublished - 2011

Publication series

NameKey Engineering Materials
Volume467-469
ISSN (Print)1013-9826
ISSN (Electronic)1662-9795

Keywords

  • Collaborative filtering
  • Context-awareness
  • Decision trees
  • Location-based advertising
  • Recommender systems

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