SRC: Incorporating Geographic Information for Building a Location-Based Recommendation System

SRC: Incorporating Geographic Information for Building a Location-Based Recommendation System. Jiao, Y. & Chiang, Y. In Proceedings of the 29th International Conference on Advances in Geographic Information Systems, of SIGSPATIAL '21, pages 680–681, New York, NY, USA, 2021. Association for Computing Machinery.

Paper doi abstract bibtex

This study proposes a novel approach for location recommendation based on content-based recommendation algorithms incorporated with geographic information. The study also analyzes the impact of various dimension reduction (DR) methods on the recommendation quality using various baseline approaches. The experiment demonstrates that the proposed approach to content-based location recommendations is feasible and valuable, with potentials for further research.

@inproceedings{10.1145/3474717.3486811,
author = {Jiao, Yuankun and Chiang, Yao-Yi},
title = {SRC: Incorporating Geographic Information for Building a Location-Based Recommendation System},
year = {2021},
isbn = {9781450386647},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3474717.3486811},
doi = {10.1145/3474717.3486811},
abstract = {This study proposes a novel approach for location recommendation based on content-based recommendation algorithms incorporated with geographic information. The study also analyzes the impact of various dimension reduction (DR) methods on the recommendation quality using various baseline approaches. The experiment demonstrates that the proposed approach to content-based location recommendations is feasible and valuable, with potentials for further research.},
booktitle = {Proceedings of the 29th International Conference on Advances in Geographic Information Systems},
pages = {680–681},
numpages = {2},
keywords = {dimension reduction, data mining, location recommendation system},
location = {Beijing, China},
series = {SIGSPATIAL '21}
}

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