Mining nearness relations from an n-grams Web corpus in geographical space

Derungs, Curdin; Purves, Ross S.

doi:10.1080/13875868.2016.1246553

Cited by 9 publications

(9 citation statements)

References 32 publications

(49 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With respect to research in GIR, we emphasise the importance of understanding ways in which other disciplines can provide theory and empirical inputs to research. For instance, systems which seek to implement methods with respect to vague spatial relationships such as near can usefully gain by understanding ways in which vagueness has been conceptualised (e.g., Fisher, 2000), explored in language and cognition (e.g., Levinson, 2003b), represented computationally (e.g., Cohn and Gotts, 1996) and analysed (e.g., Derungs and Purves, 2016).…”

Section: Discussionmentioning

confidence: 99%

Geographic Information Retrieval: Progress and Challenges in Spatial Search of Text

Purves¹,

Clough²,

Jones³

et al. 2018

Self Cite

View full text Add to dashboard Cite

Significant amounts of information available today contain references to places on earth. Traditionally such information has been held as structured data and was the concern of Geographic Information Systems (GIS). However, increasing amounts of data in the form of unstructured text are available for indexing and retrieval that also contain spatial references. This monograph describes the field of Geographic Information Retrieval (GIR) that seeks to develop spatially-aware search systems and support user's geographical information needs. Important concepts with respect to storing, querying and analysing geographical information in computers are introduced, before user needs and interaction in the context of GIR are explored. The task of associating documents with coordinates, prior to their indexing and ranking forms the core of any GIR system, and different approaches and their implications are discussed. Evaluating the resulting systems and their components, and different paradigms for doing so continue to be an important area of research in GIR and are illustrated through a number of examples. The article concludes by setting out a range of future challenges for research in this field.

show abstract

Section: Discussionmentioning

confidence: 99%

Geographic Information Retrieval: Progress and Challenges in Spatial Search of Text

Purves¹,

Clough²,

Jones³

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…In natural language texts, spatial relations are usually specified qualitatively using spatial expressions such as at, close to, to the left of, north of, etc. These expressions convey various spatial relations, whose meaning is often vague and context dependent hindering their automatic extraction and disambiguation [114,115].…”

Section: Geospatial Semantic Information Extraction and Enrichmentmentioning

confidence: 99%

A Review of Geospatial Semantic Information Modeling and Elicitation Approaches

Kokla

Guilbert

2020

IJGI

View full text Add to dashboard Cite

The present paper provides a review of two research topics that are central to geospatial semantics: information modeling and elicitation. The first topic deals with the development of ontologies at different levels of generality and formality, tailored to various needs and uses. The second topic involves a set of processes that aim to draw out latent knowledge from unstructured or semi-structured content: semantic-based extraction, enrichment, search, and analysis. These processes focus on eliciting a structured representation of information in various forms such as: semantic metadata, links to ontology concepts, a collection of topics, etc. The paper reviews the progress made over the last five years in these two very active areas of research. It discusses the problems and the challenges faced, highlights the types of semantic information formalized and extracted, as well as the methodologies and tools used, and identifies directions for future research.

show abstract

“…Place name extraction has been an important topic within the geographic information retrieval community for some time. Jones et al [40] focused on the extraction of place names and vague regions from natural language on websites, while others were able to extract spatial relations from natural language in web documents [41]. In that same thread, additional research has looked at the identification of place names based on their context within descriptive documents [42].…”

Section: Related Workmentioning

confidence: 99%

Identifying Urban Neighborhood Names through User-Contributed Online Property Listings

McKenzie

Liu

et al. 2018

IJGI

View full text Add to dashboard Cite

Neighborhoods are vaguely defined, localized regions that share similar characteristics. They are most often defined, delineated and named by the citizens that inhabit them rather than municipal government or commercial agencies. The names of these neighborhoods play an important role as a basis for community and sociodemographic identity, geographic communication and historical context. In this work, we take a data-driven approach to identifying neighborhood names based on the geospatial properties of user-contributed rental listings. Through a random forest ensemble learning model applied to a set of spatial statistics for all n-grams in listing descriptions, we show that neighborhood names can be uniquely identified within urban settings. We train a model based on data from Washington, DC, and test it on listings in Seattle, WA, and Montréal, QC. The results indicate that a model trained on housing data from one city can successfully identify neighborhood names in another. In addition, our approach identifies less common neighborhood names and suggestions of alternative or potentially new names in each city. These findings represent a first step in the process of urban neighborhood identification and delineation.

show abstract

Mining nearness relations from an n-grams Web corpus in geographical space

Cited by 9 publications

References 32 publications

Geographic Information Retrieval: Progress and Challenges in Spatial Search of Text

Geographic Information Retrieval: Progress and Challenges in Spatial Search of Text

A Review of Geospatial Semantic Information Modeling and Elicitation Approaches

Identifying Urban Neighborhood Names through User-Contributed Online Property Listings

Contact Info

Product

Resources

About