Title
Embedding Geographic Locations for Modelling the Natural Environment using Flickr Tags and Structured Data.
Abstract
Meta-data from photo-sharing websites such as Flickr can be used to obtain rich bag-of-words descriptions of geographic locations, which have proven valuable, among others, for modelling and predicting ecological features. One important insight from previous work is that the descriptions obtained from Flickr tend to be complementary to the structured information that is available from traditional scientific resources. To better integrate these two diverse sources of information, in this paper we consider a method for learning vector space embeddings of geographic locations. We show experimentally that this method improves on existing approaches, especially in cases where structured information is available.
Year
Venue
Field
2018
arXiv: Information Retrieval
Embedding,Social media,Information retrieval,Computer science,Volunteered geographic information,Data model
DocType
Volume
Citations 
Journal
abs/1810.12091
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Shelan S. Jeawak101.01
Christopher B. Jones2106795.29
Steven Schockaert34311.41