From text to landscape: locating, identifying and mapping the use of landscape features in a Swiss Alpine corpus

Derungs, Curdin; Purves, Ross S.

doi:10.1080/13658816.2013.772184

Cited by 57 publications

(44 citation statements)

References 35 publications

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“…The notion of landscape is also illuminated by the concepts of land, nature, space, and temporal elements as well as people's attitude towards them (Litton 1968, Derungs andPurves, 2013). There are many different perspectives in order to define landscape, such as recreational, silvicultural, hydrological, ecological, acoustical, and wildlife, to name a few (McGarical, 1995).…”

Section: Problem Definitionmentioning

confidence: 99%

Including Users’ Semantics in Evaluating the Credibility of Crowdsourced Landscape Descriptions

Forati

Soleimani

Karimipour

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Landscape refers to the visible features of an area of land often considered in terms of their aesthetic appeal. The spatial configurations, composition conditions and perception situations of a landscape may be described by people, which reveal how they see and percept the landscape; thus they are different from person to person depending on the way they think or experience their surroundings. Especially, when the landscape descriptions are acquired through crowdsourcing processes, it is affected by users' semantics, which results in descriptions with varying credibilities. This paper proposes an approach to consider the user's semantics in evaluating the creditability of crowdsourced landscape descriptions.

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Section: Problem Definitionmentioning

confidence: 99%

Including Users’ Semantics in Evaluating the Credibility of Crowdsourced Landscape Descriptions

Forati

Soleimani

Karimipour

et al. 2015

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The first row in Table 1 illustrates how relevance as it is commonly implemented in GIR systems can be defined as being concerned with documents (see column 'Resource' in the table) describing geographic entities (e.g., a corpus of descriptions of natural landscapes, Derungs and Purves, 2013) and the user's query (see column 'Need' in the table); both these elements are described using the topic component (see column 'Components').…”

Section: Analysis Of Relevance Conceptsmentioning

confidence: 99%

Geographic dimensions of relevance

Sabbata

Mizzaro

Reichenbacher

2015

Journal of Documentation

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Recent advances in mobile technologies led to new spatially-and context-aware definitions of relevance. In this paper, we aim to develop the conceptual framework suggested by Mizzaro (1998) further, in order to improve the characterization and classification of current and future concepts of relevance. We formalise two new dimension of relevance. The first dimension emphasizes the spatio-temporal nature of the information seeking process. The second dimension is necessary to describe how different concepts of relevance rely on different abstractions of reality.

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“…In the first step, we applied a slightly adapted version of the method described in Derungs and Purves (2014) to retrieve toponyms (e.g., cities, villages, rivers, or mountains) from the dictionary. The GIR results used in this paper differ substantially from previous publications (e.g., Bruggmann & Fabrikant, 2014b), as we employ a more recent version of the HLS, and we eliminated limiting factors in the code, which hindered the full potential of the retrieval process.…”

Section: From Gir To Spatializationmentioning

confidence: 99%

“…From a space point of view, Derungs and Purves (2014) present a consistent framework to automatically detect, disambiguate (e.g., London, UK vs. London, Ontario, Canada), and index toponyms (e.g., a city) from unstructured or semi-structured text using a gazetteer (i.e., list of potential toponyms). How to automatically retrieve and standardize temporal information (e.g., date, time, duration, etc.)…”

Section: Introductionmentioning

confidence: 99%

How does GIScience support spatio-temporal information search in the humanities?

Bruggmann

Fabrikant

2016

Spatial Cognition & Computation

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Recent text digitization efforts make it possible to extract implicit and explicit spatio-temporal information with automated methods. We propose a GIScience approach to information search and access to visually explore digital text archives typically employed in the humanities. We detail how to extract and reorganize spatio-temporal information buried in text documents about Swiss history, based on established GIScience methods, and how to present this information to target users in an empirically evaluated visual analytics interface. Early involvement of users in this user-centered interface design process significantly improved initial design ideas. With this interdisciplinary approach to spatiotemporal information exploration and search, we hope to provide the digital humanities community novel ways to access and explore large text archives containing spatio-temporal information. How does GIScience support spatio-temporal information search in the humanities?André Bruggmann and Sara I. Fabrikant University of Zurich, Department of Geography, Zurich, SwitzerlandRecent text digitization efforts make it possible to extract implicit and explicit spatio-temporal information with automated methods. We propose a GIScience approach to information search and access to visually explore digital text archives typically employed in the humanities. We detail how to extract and reorganize spatio-temporal information buried in text documents about Swiss history, based on established GIScience methods, and how to present this information to target users in an empirically evaluated visual analytics interface. Early involvement of users in this user-centered interface design process significantly improved initial design ideas. With this interdisciplinary approach to spatio-temporal information exploration and search, we hope to provide the digital humanities community novel ways to access and explore large text archives containing spatio-temporal information.

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From text to landscape: locating, identifying and mapping the use of landscape features in a Swiss Alpine corpus

Cited by 57 publications

References 35 publications

Including Users’ Semantics in Evaluating the Credibility of Crowdsourced Landscape Descriptions

Including Users’ Semantics in Evaluating the Credibility of Crowdsourced Landscape Descriptions

Geographic dimensions of relevance

How does GIScience support spatio-temporal information search in the humanities?

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