1,721,111 research outputs found
Foreword
No full textThe workshop addressed the use of geographic information systems and other spatial technologies in humanities research, bringing together researchers and practitioners from different subfields of computer science and the geographical information sciences, interested in applying spatial methods and technology to the humanities
MapReader : a computer vision pipeline for the semantic exploration of maps at scale
No full textWe present MapReader, a free, open-source software library written in Python for analyzing large map collections. MapReader allows users with little computer vision expertise to i) retrieve maps via web-servers; ii) preprocess and divide them into patches; iii) annotate patches; iv) train, fine-tune, and evaluate deep neural network models; and v) create structured data about map content. We demonstrate how MapReader enables historians to interpret a collection of ≈16K nineteenth-century maps of Britain (≈30.5M patches), foregrounding the challenge of translating visual markers into machine-readable data. We present a case study focusing on rail and buildings. We also show how the outputs from the MapReader pipeline can be linked to other, external datasets. We release ≈62K manually annotated patches used here for training and evaluating the models
Toponym disambiguation in historical documents using network analysis of qualitative relationships
No full textIn this paper we use network analysis to identify qualitative “neighbors” for toponyms in an eighteenth-century French encyclopedia, but could apply to any entry-based text with annotated toponyms. This method draws on relations in a corpus of articles, which improves disambiguation at a later stage with an external resource. We suggest the network as an alternative to geospatial representation, a useful proxy when no historical gazetteer exists for the source material’s period. Our first experiments have shown that this approach goes beyond a simple text analysis and is able to find relations between toponyms that are not co-occurring in the same documents. Network relations are also usefully compared with disambiguated toponyms to evaluate geographical coverage, and the ways that geographical discourse is expressed, in historical texts
Developing an urban gazetteer : a semantic web database for humanities data
No full textThis talk discusses the development of a spatiotemporal data model for an urban gazetteer. The function of gazetteers is to obtain descriptions uniquely identifying places referred to in discourse. Often, they are lists of places containing place name, feature type and geographical extent. Contemporary digital gazetteers (e.g. World Historical Gazetteer and Pleiades) are valuable tools for geographical knowledge of the past and the structuring of humanities data. However, scholars and GLAM (Galleries, Libraries, Archives and Museums) specialists often require information about entities on an intra-city scale. This presentation explores the model and implementation of an urban gazetteer using CIDOC CRM as a top-level ontology. The model will closely follow international gazetteer standards (i.e. Linked Places Format) in order to ensure interoperability with other gazetteer datasets. To move towards a FAIR (Findable, Accessible, Interoperable, and Reusable) approach, humanities data from the urban gazetteer will be published as Linked Open Data (LOD) and searchable via (Geo)SPARQL
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
From BERT Fine-tuning to LLM Prompting: Geospatial Named Entity Recognition in Historical French Texts
No full textInternational audienc
Evaluation of Transformer Models (from BERT to GPT) for Geographic Information Recognition
No full textInternational audienceIn this presentation, we will focus on the automatic recognition of named entities, nested named entities, nominal entities, and geographic information (spatial relationships and geographic coordinates). We will present a comparative study of different methods, with a particular focus on Transformer-based models, from BERT to GPT. The objective of this task is to extract and structure geographic information as a preliminary step for analysis tasks. In addition to evaluating automatic annotation methods, we will present the annotated dataset GeoEDdA, consisting of encyclopedic articles, which was used for training and evaluation phases. We will also present a case study on toponym resolution and mapping based on the generated data
Evaluation of Transformer Models (from BERT to GPT) for Geographic Information Recognition
No full textInternational audienceIn this presentation, we will focus on the automatic recognition of named entities, nested named entities, nominal entities, and geographic information (spatial relationships and geographic coordinates). We will present a comparative study of different methods, with a particular focus on Transformer-based models, from BERT to GPT. The objective of this task is to extract and structure geographic information as a preliminary step for analysis tasks. In addition to evaluating automatic annotation methods, we will present the annotated dataset GeoEDdA, consisting of encyclopedic articles, which was used for training and evaluation phases. We will also present a case study on toponym resolution and mapping based on the generated data
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