{"title":"Linking Spatial Named Entities to the Web of Data for Geographical Analysis of Historical Texts","authors":"Pierre-Henri Paris, N. Abadie, Carmen Brando","doi":"10.1080/15420353.2017.1307306","DOIUrl":null,"url":null,"abstract":"In our work, we are interested in facilitating the exploration by scholars of the geography of texts: in particular, historical narrative texts describing routes. Semantic annotation constitutes the first step to enrich such text with the necessary information for producing analytical maps. The present article focuses on the disambiguation of spatial named entities (SNE) by the attribution of an identifier of the ever-growing Web of Data. This giant knowledge base (KB) provides qualitative spatial information about geographic entities, in particular spatial relations such as (:Paris :southOf :Lille), (:Paris :country :France). We thus propose a graph-matching algorithm relying on the A* algorithm and graph-edit distances for choosing the best referent in the KB for the SNE. We performed preliminary experiments and noted the clear gain in performance. We propose some examples of maps that are built semi-automatically. Finally, we draw conclusions and describe our plans of future work.","PeriodicalId":54009,"journal":{"name":"Journal of Map & Geography Libraries","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/15420353.2017.1307306","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Map & Geography Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15420353.2017.1307306","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 7
Abstract
In our work, we are interested in facilitating the exploration by scholars of the geography of texts: in particular, historical narrative texts describing routes. Semantic annotation constitutes the first step to enrich such text with the necessary information for producing analytical maps. The present article focuses on the disambiguation of spatial named entities (SNE) by the attribution of an identifier of the ever-growing Web of Data. This giant knowledge base (KB) provides qualitative spatial information about geographic entities, in particular spatial relations such as (:Paris :southOf :Lille), (:Paris :country :France). We thus propose a graph-matching algorithm relying on the A* algorithm and graph-edit distances for choosing the best referent in the KB for the SNE. We performed preliminary experiments and noted the clear gain in performance. We propose some examples of maps that are built semi-automatically. Finally, we draw conclusions and describe our plans of future work.
期刊介绍:
The Journal of Map & Geography Libraries is a multidisciplinary publication that covers international research and information on the production, procurement, processing, and utilization of geographic and cartographic materials and geospatial information. Papers submitted undergo a rigorous peer-review process by professors, researchers, and practicing librarians with a passion for geography, cartographic materials, and the mapping and spatial sciences. The journal accepts original theory-based, case study, and practical papers that substantially advance an understanding of the mapping sciences in all of its forms to support users of map and geospatial collections, archives, and similar institutions.