Geographical Information Retrieval with Ontologies of Place

Jones, Christopher B.; Alani, Harith; Tudhope, Douglas

doi:10.1007/3-540-45424-1_22

Cited by 125 publications

(87 citation statements)

References 16 publications

(12 reference statements)

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“…Google's things not strings slogan implemented in their new Knowledge Graph shows semantic search in action and highlights how single pieces of data are combined and interlinked flexibly. 3 In a scientific context and combined with Big Data, semantic search and querying will go further and allow to answer complex scientific questions that span over scientific disciplines [1]. With EarthCube, NSF is currently establishing such an integrated data and service infrastructure across the geosciences.…”

Section: Publishing and Retrievingmentioning

confidence: 99%

“…With EarthCube, NSF is currently establishing such an integrated data and service infrastructure across the geosciences. New semantics-enabled geographic information retrieval paradigms employ ontologies to assist users in browsing and discovering data based on analogies and similarity reasoning [3][4][5]. To give concrete examples, the paradigm shift from data silos to interlinked and open data will support scientists in searching for appropriate study areas, in finding data sources which offer a different perspective on the same studied phenomena to gain a more holistic view, and in interlinking their own data with external datasets instead of maintaining local and aging copies.…”

Section: Publishing and Retrievingmentioning

confidence: 99%

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Key Ingredients for Your Next Semantics Elevator Talk

Janowicz

Hitzler

2012

Lecture Notes in Computer Science

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Abstract. 2012 brought a major change to the semantics research community. Discussions on the use and benefits of semantic technologies are shifting away from the why to the how. Surprisingly this more in stakeholder interest is not accompanied by a more detailed understanding of what semantics research is about. Instead of blaming others for their (wrong) expectations, we need to learn how to emphasize the paradigm shift proposed by semantics research while abstracting from technical details and advocate the added value in a way that relates to the immediate needs of individual stakeholders without overselling. This paper highlights some of the major ingredients to prepare your next Semantics Elevator Talk.

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Section: Publishing and Retrievingmentioning

confidence: 99%

Section: Publishing and Retrievingmentioning

confidence: 99%

Key Ingredients for Your Next Semantics Elevator Talk

Janowicz

Hitzler

2012

Lecture Notes in Computer Science

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“…Place names are integrated as independent dimensions in a vector space model, whereas in fact, they are points (or regions) in a two-dimensional geographical space. In order to improve such a keyword-based search method, (Cai, 2002) proposed to integrate proper ontologies of places as promoted by (Jones et al, 2001). …”

Section: Related Workmentioning

confidence: 99%

Normalizing Spatial Information to Improve Geographical Information Indexing and Retrieval in Digital Libraries

Palacio

Sallaberry

Gaio

2012

Lecture Notes in Geoinformation and Cartography

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ABSTRACT:Our contribution is dedicated to geographic information contained in unstructured textual documents. The main focus of this article is to propose a general indexing strategy that is dedicated to spatial information, but which could be applied to temporal and thematic information as well. More specifically, we have developed a process flow that indexes the spatial information contained in textual documents. This process flow interprets spatial information and computes corresponding accurate footprints. Our goal is to normalize such heterogeneous grained and scaled spatial information (points, polylines, polygons). This normalization is carried out at the index level by grouping spatial information together within spatial areas and by using statistics to compute frequencies for such areas and weights for the retrieved documents.

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“…Furthermore, authors of [8,37] de ne equations to calculate the spatial relevance when an ontology is used in the system. In [38], a proposal to combine spatial-based measures and ontology-based measures is presented. In our system, the computation of toponymRelevance q,d,l depends on whether the user speci es the spatial context for the query using a location name, selecting a node in the spatial index, or using a query window.…”

Section: Pure Spatial Queriesmentioning

confidence: 99%

Exploiting geographic references of documents in a geographical information retrieval system using an ontology-based index

et al. 2010

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Both Geographic Information Systems and Information Retrieval have been very active research elds in the last decades. Lately, a new research eld called Geographic Information Retrieval has appeared from the intersection of these two elds.The main goal of this eld is to de ne index structures and techniques to e ciently store and retrieve documents using both the text and the geographic references contained within the text. We present in this paper two contributions to this research eld. First, we propose a new index structure that combines an inverted index and a spatial index based on an ontology of geographic space. This structure improves the query capabilities of other proposals. Then, we describe the architecture of a system for geographic information retrieval that de nes a work ow for the extraction of the geographic references in documents. The architecture also uses the index structure that we propose to solve pure spatial and textual queries as well as hybrid queries that combine both a textual and a spatial component. Furthermore, query expansion can be performed on geographic references because the index structure is based in an ontology.

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Geographical Information Retrieval with Ontologies of Place

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Cited by 125 publications

References 16 publications

Key Ingredients for Your Next Semantics Elevator Talk

Key Ingredients for Your Next Semantics Elevator Talk

Normalizing Spatial Information to Improve Geographical Information Indexing and Retrieval in Digital Libraries

Exploiting geographic references of documents in a geographical information retrieval system using an ontology-based index

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