2 Search Results for "Purves, Ross S."


Document
Short Paper
Towards the Usefulness of User-Generated Content to Understand Traffic Events (Short Paper)

Authors: Rahul Deb Das and Ross S. Purves

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)


Abstract
This paper explores the usefulness of Twitter data to detect traffic events and their geographical locations in India through machine learning and NLP. We develop a classification module that can identify tweets relevant for traffic authorities with 0.80 recall accuracy using a Naive Bayes classifier. The proposed model also handles vernacular geographical aspects while retrieving place information from unstructured texts using a multi-layered georeferencing module. This work shows Mumbai has a wide spread use of Twitter for traffic information dissemination with substantial geographical information contributed by the users.

Cite as

Rahul Deb Das and Ross S. Purves. Towards the Usefulness of User-Generated Content to Understand Traffic Events (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 25:1-25:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


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@InProceedings{das_et_al:LIPIcs.GISCIENCE.2018.25,
  author =	{Das, Rahul Deb and Purves, Ross S.},
  title =	{{Towards the Usefulness of User-Generated Content to Understand Traffic Events}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{25:1--25:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.25},
  URN =		{urn:nbn:de:0030-drops-93539},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.25},
  annote =	{Keywords: Urban mobility, traffic, UGC, tweet, event, GIR, geoparsing}
}
Document
A Crowdsourced Model of Landscape Preference

Authors: Olga Chesnokova, Mario Nowak, and Ross S. Purves

Published in: LIPIcs, Volume 86, 13th International Conference on Spatial Information Theory (COSIT 2017)


Abstract
The advent of new sources of spatial data and associated information (e.g. Volunteered Geographic Information (VGI)) allows us to explore non-expert conceptualisations of space, where the number of participants and spatial extent coverage encompassed can be much greater than is available through traditional empirical approaches. In this paper we explore such data through the prism of landscape preference or scenicness. VGI in the form of photographs is particularly suited to this task, and the volume of images has been suggested as a simple proxy for landscape preference. We propose another approach, which models landscape aesthetics based on the descriptions of some 220000 images collected in a large VGI project in the UK, and more than 1.5 million votes related to the perceived scenicness of these images collected in a crowdsourcing project. We use image descriptions to build features for a supervised machine learning algorithm. Features include the most frequent uni- and bigrams, adjectives, presence of verbs of perception and adjectives from the "Landscape Adjective Checklist". Our results include not only qualitative information relating terms to scenicness in the UK, but a model based on our features which can predict some 52% of the variation in scenicness, comparable to typical models using more traditional approaches. The most useful features are the 800 most frequent unigrams, presence of adjectives from the "Landscape Adjective Checklist" and a spatial weighting term.

Cite as

Olga Chesnokova, Mario Nowak, and Ross S. Purves. A Crowdsourced Model of Landscape Preference. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 19:1-19:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


Copy BibTex To Clipboard

@InProceedings{chesnokova_et_al:LIPIcs.COSIT.2017.19,
  author =	{Chesnokova, Olga and Nowak, Mario and Purves, Ross S.},
  title =	{{A Crowdsourced Model of Landscape Preference}},
  booktitle =	{13th International Conference on Spatial Information Theory (COSIT 2017)},
  pages =	{19:1--19:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-043-9},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{86},
  editor =	{Clementini, Eliseo and Donnelly, Maureen and Yuan, May and Kray, Christian and Fogliaroni, Paolo and Ballatore, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2017.19},
  URN =		{urn:nbn:de:0030-drops-77513},
  doi =		{10.4230/LIPIcs.COSIT.2017.19},
  annote =	{Keywords: VGI, crowdsourcing, semantics, landscape preference}
}
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