6 Search Results for "Stock, Kristin"

Document
DOI: 10.4230/LIPIcs.COSIT.2022.1
What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions

Authors: Niloofar Aflaki, Kristin Stock, Christopher B. Jones, Hans Guesgen, Jeremy Morley, and Yukio Fukuzawa

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
Natural language location descriptions frequently describe object locations relative to other objects (the house near the river). Geospatial prepositions (e.g.near) are a key element of these descriptions, and the distances associated with proximity, adjacency and topological prepositions are thought to depend on the context of a specific scene. When referring to the context, we include consideration of properties of the relatum such as its feature type, size and associated image schema. In this paper, we extract spatial descriptions from the Google search engine for nine prepositions across three locations, compare their acceptance thresholds (the distances at which different prepositions are acceptable), and study variations in different contexts using cumulative graphs and scatter plots. Our results show that adjacency prepositions next to and adjacent to are used for a large range of distances, in contrast to beside; and that topological prepositions in, at and on can all be used to indicate proximity as well as containment and collocation. We also found that reference object image schema influences the selection of geospatial prepositions such as near and in.
Cite as

Niloofar Aflaki, Kristin Stock, Christopher B. Jones, Hans Guesgen, Jeremy Morley, and Yukio Fukuzawa. What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{aflaki_et_al:LIPIcs.COSIT.2022.1,
  author =	{Aflaki, Niloofar and Stock, Kristin and Jones, Christopher B. and Guesgen, Hans and Morley, Jeremy and Fukuzawa, Yukio},
  title =	{{What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{1:1--1:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.1},
  URN =		{urn:nbn:de:0030-drops-168865},
  doi =		{10.4230/LIPIcs.COSIT.2022.1},
  annote =	{Keywords: contextual factors, spatial descriptions, acceptance model, spatial template, applicability model, geospatial prepositions}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2022.4
Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections

Authors: Ruoxuan Liao, Pragyan P. Das, Christopher B. Jones, Niloofar Aflaki, and Kristin Stock

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
A considerable proportion of records that describe biological specimens (flora, soil, invertebrates), and especially those that were collected decades ago, are not attached to corresponding geographical coordinates, but rather have their location described only through textual descriptions (e.g. North Canterbury, Selwyn River near bridge on Springston-Leeston Rd). Without geographical coordinates, millions of records stored in museum collections around the world cannot be mapped. We present a method for predicting the distance and direction associated with human language location descriptions which focuses on the interpretation of geospatial prepositions and the way in which they modify the location represented by an associated reference place name (e.g. near the Manawatu River). We study eight distance-oriented prepositions and eight direction-oriented prepositions and use machine learning regression to predict distance or direction, relative to the reference place name, from a collection of training data. The results show that, compared with a simple baseline, our model improved distance predictions by up to 60% and direction predictions by up to 31%.
Cite as

Ruoxuan Liao, Pragyan P. Das, Christopher B. Jones, Niloofar Aflaki, and Kristin Stock. Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{liao_et_al:LIPIcs.COSIT.2022.4,
  author =	{Liao, Ruoxuan and Das, Pragyan P. and Jones, Christopher B. and Aflaki, Niloofar and Stock, Kristin},
  title =	{{Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{4:1--4:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.4},
  URN =		{urn:nbn:de:0030-drops-168892},
  doi =		{10.4230/LIPIcs.COSIT.2022.4},
  annote =	{Keywords: geospatial prepositions, biological specimen collections, georeferencing, natural language processing, locative expressions, locality descriptions, geoparsing, geocoding, geographic information retrieval, regression, machine learning}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.13
Automated Georeferencing of Antarctic Species

Authors: Jamie Scott, Kristin Stock, Fraser Morgan, Brandon Whitehead, and David Medyckyj-Scott

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II

Abstract
Many text documents in the biological domain contain references to the toponym of specific phenomena (e.g. species sightings) in natural language form "In <LOCATION> Garwood Valley summer activity was 0.2% for <SPECIES> Umbilicaria aprina and 1.7% for <SPECIES> Caloplaca sp. ..." While methods have been developed to extract place names from documents, and attention has been given to the interpretation of spatial prepositions, the ability to connect toponym mentions in text with the phenomena to which they refer (in this case species) has been given limited attention, but would be of considerable benefit for the task of mapping specific phenomena mentioned in text documents. As part of work to create a pipeline to automate georeferencing of species within legacy documents, this paper proposes a method to: (1) recognise species and toponyms within text and (2) match each species mention to the relevant toponym mention. Our methods find significant promise in a bespoke rules- and dictionary-based approach to recognise species within text (F1 scores up to 0.87 including partial matches) but less success, as yet, recognising toponyms using multiple gazetteers combined with an off the shelf natural language processing tool (F1 up to 0.62). Most importantly, we offer a contribution to the relatively nascent area of matching toponym references to the object they locate (in our case species), including cases in which the toponym and species are in different sentences. We use tree-based models to achieve precision as high as 0.88 or an F1 score up to 0.68 depending on the downsampling rate. Initial results out perform previous research on detecting entity relationships that may cross sentence boundaries within biomedical text, and differ from previous work in specifically addressing species mapping.
Cite as

Jamie Scott, Kristin Stock, Fraser Morgan, Brandon Whitehead, and David Medyckyj-Scott. Automated Georeferencing of Antarctic Species. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 13:1-13:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{scott_et_al:LIPIcs.GIScience.2021.II.13,
  author =	{Scott, Jamie and Stock, Kristin and Morgan, Fraser and Whitehead, Brandon and Medyckyj-Scott, David},
  title =	{{Automated Georeferencing of Antarctic Species}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{13:1--13:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.13},
  URN =		{urn:nbn:de:0030-drops-147726},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.13},
  annote =	{Keywords: Named Entity Recognition (NER), Taxonomic Name Extraction, Relation Extraction, Georeferencing}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2019.9
Cross-Corpora Analysis of Spatial Language: The Case of Fictive Motion (Short Paper)

Authors: Ekaterina Egorova, Niloofar Aflaki, Cristiane K. Marchis Fagundes, and Kristin Stock

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
The way people describe where things are is one of the central questions of spatial information theory and has been the subject of considerable research. We investigate one particular type of location description, fictive motion (as in, The range runs along the coast). The use of this structure is known to highlight particular properties of the described entity, as well as to convey its configuration in physical space in an effective way. We annotated 496 fictive motion structures in seven corpora that represent different types of spatial discourse – news, travel blogs, texts describing outdoor pursuits and local history, as well as image and location descriptions. We analysed the results not only by examining the distribution of fictive motion structures across corpora, but also by exploring and comparing the semantic categories of verbs used in fictive motion. Our findings, first, add to our knowledge of location description strategies that go beyond prototypical locative phrases. They further reveal how the use of fictive motion varies across types of spatial discourse and reflects the nature of the described environment. Methodologically, we highlight the benefits of a cross-corpora analysis in the study of spatial language use across a variety of contexts.
Cite as

Ekaterina Egorova, Niloofar Aflaki, Cristiane K. Marchis Fagundes, and Kristin Stock. Cross-Corpora Analysis of Spatial Language: The Case of Fictive Motion (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 9:1-9:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{egorova_et_al:LIPIcs.COSIT.2019.9,
  author =	{Egorova, Ekaterina and Aflaki, Niloofar and Fagundes, Cristiane K. Marchis and Stock, Kristin},
  title =	{{Cross-Corpora Analysis of Spatial Language: The Case of Fictive Motion}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{9:1--9:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.9},
  URN =		{urn:nbn:de:0030-drops-111011},
  doi =		{10.4230/LIPIcs.COSIT.2019.9},
  annote =	{Keywords: spatial language, spatial discourse, fictive motion, location, cross-corpora analysis}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2019.11
Detecting the Geospatialness of Prepositions from Natural Language Text (Short Paper)

Authors: Mansi Radke, Prarthana Das, Kristin Stock, and Christopher B. Jones

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
There is increasing interest in detecting the presence of geospatial locative expressions that include spatial relation terms such as near or within <some distance>. Being able to do so provides a foundation for interpreting relative descriptions of location and for building corpora that facilitate the development of methods for spatial relation extraction and interpretation. Here we evaluate the use of a spatial role labelling procedure to distinguish geospatial uses of prepositions from other spatial and non-spatial uses and experiment with the use of additional machine learning features to improve the quality of detection of geospatial prepositions. An annotated corpus of nearly 2000 instances of preposition usage was created for training and testing the classifiers.
Cite as

Mansi Radke, Prarthana Das, Kristin Stock, and Christopher B. Jones. Detecting the Geospatialness of Prepositions from Natural Language Text (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 11:1-11:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{radke_et_al:LIPIcs.COSIT.2019.11,
  author =	{Radke, Mansi and Das, Prarthana and Stock, Kristin and Jones, Christopher B.},
  title =	{{Detecting the Geospatialness of Prepositions from Natural Language Text}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{11:1--11:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.11},
  URN =		{urn:nbn:de:0030-drops-111033},
  doi =		{10.4230/LIPIcs.COSIT.2019.11},
  annote =	{Keywords: spatial language, natural language processing, geospatial language}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.20
Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions (Short Paper)

Authors: Niloofar Aflaki, Shaun Russell, and Kristin Stock

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

Abstract
In order to extract and map location information from natural language descriptions, a first step is to identify different language elements within the descriptions. In this paper, we describe a method and discuss the challenges faced in creating an annotated set of geospatial natural language descriptions using manual tagging, with the purpose of supporting validation and machine learning approaches to annotation and text interpretation.
Cite as

Niloofar Aflaki, Shaun Russell, and Kristin Stock. Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 20:1-20:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{aflaki_et_al:LIPIcs.GISCIENCE.2018.20,
  author =	{Aflaki, Niloofar and Russell, Shaun and Stock, Kristin},
  title =	{{Challenges in Creating an Annotated Set of Geospatial Natural Language Descriptions}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{20:1--20:6},
  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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.20},
  URN =		{urn:nbn:de:0030-drops-93482},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.20},
  annote =	{Keywords: Annotation challenges, spatial relations, spatial language}
}
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