Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/1197
Title: Using latent semantic analysis to identify research trends in OpenStreetMap
Authors: Sehra S.S
Singh J
Rai H.S.
Keywords: Latent semantic analysis
OpenStreetMap
Research trends
Volunteered geographic information
Issue Date: 2017
Publisher: MDPI AG
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. � 2017 by the authors. Licensee MDPI.
URI: 10.3390/ijgi6070195
http://hdl.handle.net/123456789/1197
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