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Published VersionCC BY V4.0, Open Access
Journal article
An End-to-End Point of Interest (POI) Conflation Framework
ISPRS International Journal of Geo-Information, Vol.10(11), pp.1-23
2021
Abstract
Point of interest (POI) data serves as a valuable source of semantic information for places of interest and has many geospatial applications in real estate, transportation, and urban planning. With the availability of different data sources, POI conflation serves as a valuable technique for enriching data quality and coverage by merging the POI data from multiple sources. This study proposes a novel end-to-end POI conflation framework consisting of six steps, starting with data procurement, schema standardisation, taxonomy mapping, POI matching, POI unification, and data verification. The feasibility of the proposed framework was demonstrated in a case study conducted in the eastern region of Singapore, where the POI data from five data sources was conflated to form a unified POI dataset. Based on the evaluation conducted, the resulting unified dataset was found to be more comprehensive and complete than any of the five POI data sources alone. Furthermore, the proposed approach for identifying POI matches between different data sources outperformed all baseline approaches with a matching accuracy of 97.6% with an average run time below 3 min when matching over 12,000 POIs to result in 8699 unique POIs, thereby demonstrating the framework's scalability for large scale implementation in dense urban contexts.
Details
- Title
- An End-to-End Point of Interest (POI) Conflation Framework
- Authors
- Raymond Low - Singapore University of Technology and DesignZeynep Duygu Tekler - National University of SingaporeLynette Cheah (Corresponding Author) - Singapore University of Technology and Design
- Publication details
- ISPRS International Journal of Geo-Information, Vol.10(11), pp.1-23
- Publisher
- MDPI AG
- Date published
- 2021
- DOI
- 10.3390/ijgi10110779
- ISSN
- 2220-9964
- Copyright note
- © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- OpenStreetMap data analyzed in this study is publicly available.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991029280802621
- Output Type
- Journal article
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- Collaboration types
- Domestic collaboration
- Web Of Science research areas
- Computer Science, Information Systems
- Geography, Physical
- Remote Sensing
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