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ISPRS Int. J. Geo-Inf. 2017, 6(7), 195; doi:10.3390/ijgi6070195

Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap

1
Department of Research, Innovation & Consultancy, I.K. Gujral Punjab Technical University, Kapurthala, Punjab 144603, India
2
Department of Computer Science & Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, India
3
School of Computer Sciences, Chitkara University, Patiala, Punjab 140401, India
4
Department of Civil Engineering, Guru Nanak Dev Engineering College, Ludhiana, Punjab 141006, India
*
Author to whom correspondence should be addressed.
Academic Editors: Bernd Resch, Linda See and Wolfgang Kainz
Received: 13 May 2017 / Revised: 28 June 2017 / Accepted: 28 June 2017 / Published: 1 July 2017
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Abstract

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. View Full-Text
Keywords: OpenStreetMap; research trends; latent semantic analysis; volunteered geographic information OpenStreetMap; research trends; latent semantic analysis; volunteered geographic information
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Sehra, S.S.; Singh, J.; Rai, H.S. Using Latent Semantic Analysis to Identify Research Trends in OpenStreetMap. ISPRS Int. J. Geo-Inf. 2017, 6, 195.

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