Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap
OpenStreetMap (OSM), based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA) to help identify the emerging research trends in OS...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-07-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/6/7/195 |
| _version_ | 1818064126486773760 |
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| author | Sukhjit Singh Sehra Jaiteg Singh Hardeep Singh Rai |
| author_facet | Sukhjit Singh Sehra Jaiteg Singh Hardeep Singh Rai |
| author_sort | Sukhjit Singh Sehra |
| collection | DOAJ |
| description | OpenStreetMap (OSM), based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA) to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007–2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research. |
| first_indexed | 2024-12-10T14:31:02Z |
| format | Article |
| id | doaj.art-00bcf783ed5c4a9099a2dd10d1906339 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-10T14:31:02Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-00bcf783ed5c4a9099a2dd10d19063392022-12-22T01:44:55ZengMDPI AGISPRS International Journal of Geo-Information2220-99642017-07-016719510.3390/ijgi6070195ijgi6070195Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMapSukhjit Singh Sehra0Jaiteg Singh1Hardeep Singh Rai2Department of Research, Innovation & Consultancy, I.K. Gujral Punjab Technical University, Kapurthala, Punjab 144603, IndiaSchool of Computer Sciences, Chitkara University, Patiala, Punjab 140401, IndiaDepartment of Civil Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, IndiaOpenStreetMap (OSM), based on collaborative mapping, has become a subject of great interest to the academic community, resulting in a considerable body of literature produced by many researchers. In this paper, we use Latent Semantic Analysis (LSA) to help identify the emerging research trends in OSM. An extensive corpus of 485 academic abstracts of papers published during the period 2007–2016 was used. Five core research areas and fifty research trends were identified in this study. In addition, potential future research directions have been provided to aid geospatial information scientists, technologists and researchers in undertaking future OSM research.https://www.mdpi.com/2220-9964/6/7/195OpenStreetMapresearch trendslatent semantic analysisvolunteered geographic information |
| spellingShingle | Sukhjit Singh Sehra Jaiteg Singh Hardeep Singh Rai Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap ISPRS International Journal of Geo-Information OpenStreetMap research trends latent semantic analysis volunteered geographic information |
| title | Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap |
| title_full | Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap |
| title_fullStr | Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap |
| title_full_unstemmed | Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap |
| title_short | Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap |
| title_sort | using latent semantic analysis to identify research trends in openstreetmap |
| topic | OpenStreetMap research trends latent semantic analysis volunteered geographic information |
| url | https://www.mdpi.com/2220-9964/6/7/195 |
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