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Analysis of Points of Interests Recommended for Leisure Walk Descriptions

Authors Ehsan Hamzei , Thi Minh Hoai Bui , Martin Tomko , Stephan Winter

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Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
  • Information systems → Location based services
Keywords
  • leisure walks
  • points of interest
  • places
  • platial information

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Abstract

Leisure walking is a physical activity where locomotion through a natural or even urban environment is the goal in itself, e.g., in pursuit of health and wellbeing. In contrast to destination-oriented walks that are focused on navigation efficiency (i.e., shortest or simplest walk from source to destination), leisure walks emphasize experiencing the environment, engaging in activities, and discovering places that may be off route, or intermediate destinations en-route, summarily called points of interest (POIs). POIs are key for recommending leisure walks, yet a detailed analysis of POIs in the context of leisure walking is missing in the literature. This study extracts and annotates POIs of leisure walking recommendations available in WalkingMaps.com.au, creating an annotated dataset to address this research gap and provide a first analysis of leisure walking descriptions. We classify POIs using the verbal description provided in the dataset, match them with data available in OpenStreetMap (OSM), and compare the POIs with nearby alternatives in OSM. Our analysis reveals thematic and spatial patterns in POI selection, offering a machine learning approach to model POI choices for leisure walks. We further evaluate the availability of rich data in OSM for future automated leisure walking recommendation. This study contributes to automated systems for recommending leisure walks, tailoring suggestions based on available information in the spatial open data, and presents an annotated dataset to facilitate future research in this field.

Cite As Get BibTex

Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter. Analysis of Points of Interests Recommended for Leisure Walk Descriptions. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.GIScience.2025.5

Author Details

Ehsan Hamzei
  • University of Melbourne, Parkville, Australia
Thi Minh Hoai Bui
  • University of Melbourne, Parkville, Australia
Martin Tomko
  • University of Melbourne, Parkville, Australia
Stephan Winter
  • University of Melbourne, Parkville, Australia

Supplementary Materials

References

  1. Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, and Tong Wang. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset, 2018. URL: https://arxiv.org/abs/1611.09268.
  2. Ricardo J. G. B. Campello, Davoud Moulavi, and Joerg Sander. Density-based clustering based on hierarchical density estimates. In Jian Pei, Vincent S. Tseng, Longbing Cao, Hiroshi Motoda, and Guandong Xu, editors, Advances in Knowledge Discovery and Data Mining, pages 160-172, Berlin, Heidelberg, 2013. Springer Berlin Heidelberg. Google Scholar
  3. Buru Chang, Yonggyu Park, Donghyeon Park, Seongsoon Kim, and Jaewoo Kang. Content-aware hierarchical point-of-interest embedding model for successive POI recommendation. In Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI'18, pages 3301-3307. AAAI Press, 2018. URL: https://doi.org/10.24963/IJCAI.2018/458.
  4. Harald Cramér. Mathematical Methods of Statistics. Princeton University Press, 1946. Google Scholar
  5. Song Gao, Krzysztof Janowicz, and Helen Couclelis. Extracting urban functional regions from points of interest and human activities on location-based social networks. Transactions in GIS, 21(3):446-467, 2017. URL: https://doi.org/10.1111/TGIS.12289.
  6. Yunfan Gao, Yun Xiong, Siqi Wang, and Haofen Wang. Geobert: pre-training geospatial representation learning on point-of-interest. Applied Sciences, 12(24):12942, 2022. Google Scholar
  7. Maarten Grootendorst. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794, 2022. URL: https://doi.org/10.48550/arXiv.2203.05794.
  8. Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter. hamzeiehsan/leisure-walking-analysis. Software, (visited on 2025-07-30). URL: https://github.com/hamzeiehsan/leisure-walking-analysis
    Software Heritage Logo archived version
    full metadata available at: https://doi.org/10.4230/artifacts.24214
  9. Charlie Hewitt, SD Sabbata, A Ballatore, S Cavazzi, and Nicholas Tate. Defining natural points of interest. In 29th Annual GIS Research UK Conference (GISRUK). Cardiff, Wales, UK (Online), 2021. Google Scholar
  10. Olga Koblet and Ross S. Purves. From online texts to landscape character assessment: Collecting and analysing first-person landscape perception computationally. Landscape and Urban Planning, 197:103757, 2020. URL: https://doi.org/10.1016/j.landurbplan.2020.103757.
  11. Kang Liu, Ling Yin, Feng Lu, and Naixia Mou. Visualizing and exploring POI configurations of urban regions on POI-type semantic space. Cities, 99:102610, 2020. URL: https://doi.org/10.1016/j.cities.2020.102610.
  12. Scott M Lundberg and Su-In Lee. A unified approach to interpreting model predictions. In I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, editors, Advances in Neural Information Processing Systems 30, pages 4765-4774. Curran Associates, Inc., 2017. Google Scholar
  13. Nora Fagerholm Manuel F. Baer, Flurina Wartmann and Ross S. Purves. Extracting sensory experiences and cultural ecosystem services from actively crowdsourced descriptions of everyday lived landscapes. Ecosystems and People, 20(1):2331761, 2024. URL: https://doi.org/10.1080/26395916.2024.2331761.
  14. L. McInnes, J. Healy, and J. Melville. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. ArXiv e-prints, February 2018. URL: https://arxiv.org/abs/1802.03426.
  15. Grant McKenzie and Krzysztof Janowicz. OpenPOI: An open place of interest platform (Short paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2018. URL: https://doi.org/10.4230/LIPIcs.GISCIENCE.2018.47.
  16. Achilleas Psyllidis, Song Gao, Yingjie Hu, Eun-Kyeong Kim, Grant McKenzie, Ross Purves, May Yuan, and Clio Andris. Points of Interest (POI): A commentary on the state of the art, challenges, and prospects for the future. Computational Urban Science, 2(1):20, 2022. Google Scholar
  17. Daniele Quercia, Rossano Schifanella, and Luca Maria Aiello. The shortest path to happiness: Recommending beautiful, quiet, and happy routes in the city. In Proceedings of the 25th ACM Conference on Hypertext and Social Media, pages 116-125, 2014. URL: https://doi.org/10.1145/2631775.2631799.
  18. Nils Reimers and Iryna Gurevych. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, November 2019. URL: https://doi.org/10.18653/V1/D19-1410.
  19. Tiina Sarjakoski, Pyry Kettunen, Hanna-Marika Halkosaari, Mari Laakso, Mikko Rönneberg, Hanna Stigmar, and Tapani Sarjakoski. Landmarks and a hiking ontology to support wayfinding in a national park during different seasons. In Martin Raubal, David M. Mark, and Andrew U. Frank, editors, Cognitive and Linguistic Aspects of Geographic Space: New Perspectives on Geographic Information Research, pages 99-119. Springer Berlin Heidelberg, Berlin, Heidelberg, 2013. URL: https://doi.org/10.1007/978-3-642-34359-9_6.
  20. Nancy Stevenson and Helen Farrell. Taking a hike: exploring leisure walkers embodied experiences. Social & Cultural Geography, 19(4):429-447, 2018. URL: https://doi.org/10.1080/14649365.2017.1280615.
  21. Demi van Weerdenburg, Simon Scheider, Benjamin Adams, Bas Spierings, and Egbert van der Zee. Where to go and what to do: Extracting leisure activity potentials from web data on urban space. Computers, Environment and Urban Systems, 73:143-156, 2019. URL: https://doi.org/10.1016/J.COMPENVURBSYS.2018.09.005.
  22. James Williams, Stefano Cavazzi, James Pinchin, Adrian Hazzard, Gary Priestnall, and Andrea Ballatore. Context for leisure walking routes: A vision for a spatial-platial approach. In Spatial Data Science Symposium 2022 Short Paper Proceedings, 2022. URL: https://doi.org/10.25436/E20W2J.
  23. James Williams, James Pinchin, Adrian Hazzard, Gary Priestnall, Stefano Cavazzi, and Andrea Ballatore. Emerging platial narratives and themes from a leisure walking study. In Proceedings of the 4th International Symposium on Platial Information Science (PLATIAL’23), pages 23-28, 2023. Google Scholar
  24. James Williams, James Pinchin, Adrian Hazzard, Gary Priestnall, Stefano Cavazzi, and Andrea Ballatore. Walkgis: Exploring platial analysis of leisure walks via linked video narratives. In 31st Annual Geographical Information Science Research UK Conference (GISRUK), 2023. Google Scholar
  25. Stephan Winter, Ehsan Hamzei, Nico Van de Weghe, and Kristien Ooms. A graph representation for verbal indoor route descriptions. In Sarah Creem-Regehr, Johannes Schöning, and Alexander Klippel, editors, Spatial Cognition XI, pages 77-91, Cham, 2018. Springer International Publishing. URL: https://doi.org/10.1007/978-3-319-96385-3_6.
  26. Lih Wei Yeow, Raymond Low, Yu Xiang Tan, and Lynette Cheah. Point-of-Interest (POI) Data Validation Methods: An Urban Case Study. ISPRS International Journal of Geo-Information, 10(11), 2021. URL: https://doi.org/10.3390/ijgi10110735.
  27. Kangzhi Zhao, Yong Zhang, Hongzhi Yin, Jin Wang, Kai Zheng, Xiaofang Zhou, and Chunxiao Xing. Discovering subsequence patterns for next POI recommendation. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence, pages 3216-3222, 2021. Google Scholar
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