Embedding geographic locations for modelling the natural environment using flickr tags and structured data

Jeawak, Shelan S.; Jones, Christopher B.; Schockaert, Steven

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.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: European Conference on Information Retrieval
• Start Date: Apr 14, 2019
• End Date: Apr 18, 2019
• Acceptance Date: Apr 1, 2019
• Online Publication Date: Apr 7, 2019
• Publication Date: Apr 7, 2019
• Deposit Date: Jun 5, 2020
• Publisher: Springer Verlag
• Volume: 11437
• Pages: 51-66
• Series Title: Lecture Notes in Computer Science
• Book Title: Advances in Information Retrieval
• ISBN: 9783030157111
• DOI: https://doi.org/10.1007/978-3-030-15712-8_4
• Keywords: Social media, Text mining, Vector space embeddings, Volunteered geographic information, Ecology
• Public URL: https://uwe-repository.worktribe.com/output/5986220
• Additional Information: First Online: 7 April 2019; Conference Acronym: ECIR; Conference Name: European Conference on Information Retrieval; Conference City: Cologne; Conference Country: Germany; Conference Year: 2019; Conference Start Date: 14 April 2019; Conference End Date: 18 April 2019; Conference Number: 41; Conference ID: ecir2019; Conference URL: https://ecir2019.org/