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Building Type Classification from Social Media Texts via geo-spatial Textmining

Häberle, Matthias and Werner, Martin and Zhu, Xiao Xiang (2019) Building Type Classification from Social Media Texts via geo-spatial Textmining. In: 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 1-4. IGARSS 2019, 28. Juli - 02. Aug. 2019, Yokohama, Japan.

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Official URL: https://igarss2019.org/

Abstract

In this work, we present a model for building type classifica tion from Twitter text messages (tweets) by employing geo-spatial text mining methods. First, we apply standard text pre-processing methods and convert the tweets into sentence vectors using fastText. For classification, we apply a feedforward network with two fully connected hidden layers and feed the generated sentence vectors as linguistic features. Classification results suggest that the classes are distinguishable to a certain extent with pure text even with unbalanced class distributions and a very small sample size. However, these findings also undermine, that building type classification with pure text data is a challenging task.

Item URL in elib:https://elib.dlr.de/127637/
Document Type:Conference or Workshop Item (Poster)
Title:Building Type Classification from Social Media Texts via geo-spatial Textmining
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Häberle, MatthiasMatthias.Haeberle (at) dlr.dehttps://orcid.org/0000-0001-9550-5252
Werner, MartinMartin.Werner (at) dlr.deUNSPECIFIED
Zhu, Xiao Xiangxiaoxiang.zhu (at) dlr.dehttps://orcid.org/0000-0001-5530-3613
Date:2019
Journal or Publication Title:2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-4
Status:Published
Keywords:Urban Remote Sensing, Building Settlement Type, Classification, Natural Language Processing, Deep Learning, Word Embedding, Language, Social Media, Data Mining
Event Title:IGARSS 2019
Event Location:Yokohama, Japan
Event Type:international Conference
Event Dates:28. Juli - 02. Aug. 2019
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > EO Data Science
Deposited By: Häberle, Matthias
Deposited On:28 Jun 2019 10:17
Last Modified:06 Dec 2019 18:00

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