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Publication Detail
Lower dimensional representations of city neighbourhoods
  • Publication Type:
    Conference
  • Authors:
    Saeidi M, Riedel S, Capra L
  • Publication date:
    01/01/2015
  • Pagination:
    56, 59
  • Published proceedings:
    AAAI Workshop - Technical Report
  • Volume:
    WS-15-04
  • ISBN-13:
    9781577357155
  • Status:
    Published
Abstract
© 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.We aim to profile characteristics of areas of variant units across a district, city or a country. Studying attributes of areas can be very useful in several situations. In the past, research has focused mainly on studying specific charcteristics of areas using a few selected attributes. In this paper we propose an alternative view on neighbourhood profiles. Instead of characterising a neighbourhood through a set of attributes such as those collected by the census, we propose use of a low-dimensional feature representation, or embedding, created from one or more input sources. The purpose of the embeddings is having a generic representation for entities that can do well across several downstream tasks such as regression for attributes prediction.
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