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2017 | OriginalPaper | Chapter

Behavior-Based Location Recommendation on Location-Based Social Networks

Authors : Seyyed Mohammadreza Rahimi, Xin Wang, Behrouz Far

Published in: Advances in Knowledge Discovery and Data Mining

Publisher: Springer International Publishing

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Abstract

Location recommendation makes suggestions of nearby locations based on user’s locational preferences and spatial movement patterns. In this paper, we propose two novel location recommendation methods called Behavior Factorization (BF) and Latent Behavior Analysis (LBA). Both methods utilize behavioral and spatio-temporal patterns in user movements to make location recommendation. Experiments on a real-world dataset shows that the proposed methods outperform existing location recommendation methods in terms of both precision and recall. Comparing LBA and BF, it is observed that LBA achieves better results since it utilizes the number of times each pattern has happened in the dataset.

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previous chapter Efficient Training of Adaptive Regularization of Weight Vectors for Semi-structured Text
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Footnotes
1
A location-based social networking website that in operation until 2012.
 
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Metadata
Title
Behavior-Based Location Recommendation on Location-Based Social Networks
Authors
Seyyed Mohammadreza Rahimi
Xin Wang
Behrouz Far
Copyright Year
2017
Book
Advances in Knowledge Discovery and Data Mining

Print ISBN: 978-3-319-57528-5

Electronic ISBN: 978-3-319-57529-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-57529-2_22

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