@inproceedings{eff2e563bd42427bb6cc159a86680f15,
title = "Context-aware recommender system for location-based advertising",
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.",
keywords = "Collaborative filtering, Context-awareness, Decision trees, Location-based advertising, Recommender systems",
author = "Hyunchul Ahn and Kim, {Kyoung Jae}",
year = "2011",
doi = "10.4028/www.scientific.net/KEM.467-469.2091",
language = "English",
isbn = "9783037850176",
series = "Key Engineering Materials",
publisher = "Trans Tech Publications Ltd",
pages = "2091--2096",
booktitle = "Materials, Mechatronics and Automation",
address = "Switzerland",
}