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Generating geographical location descriptions with spatial templates: a salient toponym driven approach / Mark M. Hall in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 55 - 85 Titre : Generating geographical location descriptions with spatial templates: a salient toponym driven approach Type de document : Article/Communication Auteurs : Mark M. Hall, Auteur ; Christopher B. Jones, Auteur Année de publication : 2022 Article en page(s) : pp 55 - 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Toponymie [Termes IGN] image Flickr [Termes IGN] OpenStreetMap [Termes IGN] relation spatiale [Termes IGN] répertoire toponymique [Termes IGN] saillance [Termes IGN] toponyme [Termes IGN] traitement du langage naturel Résumé : (auteur) Natural language descriptions of geographical locations are used frequently in daily life and there is a motivation to create systems that generate such descriptions automatically, for purposes such as documentation of where events have taken place, where a person is located, where photos were taken and where plants and animals are located. Typically location descriptions combine references to named geographical features with vague spatial relational terms, such as near, north of and at that relate locations to the features. Here we describe a system for generating location descriptions, that combines spatial templates, that model the applicability of different spatial relations relative to a reference location, with toponyms in the vicinity of the described location that are selected according to aspects of salience. The toponyms are retrieved from a gazetteer service based on OpenStreetMap for which we create a hierarchical feature classification scheme to facilitate selection of toponyms according to distinctiveness of their feature types and other aspects of salience. The advantages of the approach are demonstrated in a user study, relative to an existing state of the art system and to other baseline approaches that include manually created captions and the automated methods of two widely used photo captioning systems. Numéro de notice : A2022-043 Affiliation des auteurs : non IGN Thématique : TOPONYMIE Nature : Article DOI : 10.1080/13658816.2021.1913498 Date de publication en ligne : 28/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1913498 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99402 [article]

Extracting event-related information from a corpus regarding soil industrial pollution / Chuanming Dong (2021)  

Public Titre : Extracting event-related information from a corpus regarding soil industrial pollution Type de document : Article/Communication Auteurs : Chuanming Dong, Auteur ; Philippe Gambette, Auteur ; Catherine Dominguès , Auteur Editeur : Setúbal [Portugal] : Science and Technology Publications - Scitepress Année de publication : 2021 Projets : 1-Pas de projet / Conférence : KDIR 2021, 13th International Conference on Knowledge Discovery and Information Retrieval 25/10/2021 27/10/2021 Setubal Portugal OA Proceedings Importance : pp 217 - 224 Note générale : bibliographie In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR, ISBN 978-989-758-533-3 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] apprentissage profond [Termes IGN] corpus [Termes IGN] extraction automatique [Termes IGN] pollution des sols [Termes IGN] traitement du langage naturel Résumé : (auteur) We study the extraction and reorganization of event-related information in texts regarding industrial pollution. The object is to build a memory of polluted sites that gathers the information about industrial events from various databases and corpora. An industrial event is described through several features as the event trigger, the industrial activity, the institution, the pollutant, etc. In order to efficiently collect information from a large corpus, it is necessary to automatize the information extraction process. To this end, we manually annotated a part of a corpus about soil industrial pollution, then we used it to train information extraction models with deep learning methods. The models we trained achieve 0.76 F-score on event feature extraction. We intend to improve the models and then use them on other text resources to enrich the polluted sites memory with extracted information about industrial events. Numéro de notice : C2021-068 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5220/0010656700003064 En ligne : https://dx.doi.org/10.5220/0010656700003064 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99540

Le carrefour dont vous êtes le héros : description de carrefours pour les personnes déficientes visuelles / Jérémy Kalsron (2021)    

Public Titre : Le carrefour dont vous êtes le héros : description de carrefours pour les personnes déficientes visuelles Type de document : Article/Communication Auteurs : Jérémy Kalsron, Auteur ; Jean-Marie Favreau, Auteur ; Guillaume Touya , Auteur Editeur : Paris, Toulouse, ... : Centre national de la recherche scientifique CNRS Année de publication : 2021 Projets : ACTIVmap / Favreau, Jean-Marie Conférence : SAGEO 2021, 16th spatial analysis and geomatics conference 05/05/2021 07/05/2021 La Rochelle en ligne France open access proceedings Importance : pp 271 - 273 Langues : Français (fre) Descripteur : [Termes IGN] carrefour [Termes IGN] malvoyant [Termes IGN] modèle conceptuel de données localisées [Termes IGN] traitement du langage naturel Mots-clés libres : génération automatique de texte Numéro de notice : C2021-021 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Poster nature-HAL : Poster-avec-CL DOI : sans En ligne : https://apps.univ-lr.fr/actes/ged/colloques/docWeb/2105041945.0/SAGEO2021_Actes_ [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98253

Documents numériques

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Place names in Spanish republican life stories: spatial patterns in locations and perceptions / Laurence Jolivet (2021)  

Public Titre : Place names in Spanish republican life stories: spatial patterns in locations and perceptions Type de document : Article/Communication Auteurs : Laurence Jolivet , Auteur ; Carmen Brando , Auteur ; Catherine Dominguès , Auteur Editeur : Paris, ... [Suède] : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Proceedings of the ICA num. 4 Projets : MATRICIEL / Favreau, Jean-Marie Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie open access proceedings Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] analyse spatiale [Termes IGN] corpus [Termes IGN] récit [Termes IGN] toponyme [Termes IGN] traitement du langage naturel Mots-clés libres : local Moran’s index = indice local de Moran Résumé : (auteur) Places can be defined by different features including geographical coordinates, landscape elements and also subjective information like perception. The corpus collected by the Réseau des acteurs de l’histoire et la mémoire de l’immigration (RAHMI) contains oral interviews about Spanish Republicans journeys during Spanish Civil War and World War II. These life stories quote place names corresponding to proper name (Npr) or common name (Nc) and which can be qualified or associated to non-geographical nouns, adjectives and expressions. Methods from natural language processing have been used to automatically extract and characterize these pieces of informations into annotations. The objective of the presented work is to analyse the geographical aspects of places and associated features, and to propose cartographical displays illustrating life stories and supporting analysis. Distribution of quoted Npr place names was first studied. It enabled targeting relevant spatial scales and so mapping extents for the corpus. Second, features of Npr places about their type (administrative, topographic) and their spatial target based on assocations with Nc have been synthetized. Then perception were allocated to Npr, falling into the three values of polarity positive, negative or neutral. Spatial patterns of each value have been displayed and interpreted. Summary of the annotations, analysis and created maps offer insights into the corpus driven by the mentioned places. Based on individual testimonies, it may help further interpretation and researches about this historical period. Numéro de notice : C2021-059 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-4-49-2021 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.5194/ica-proc-4-49-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99433

Social media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? / Oliver Lock in Geo-spatial Information Science, vol 23 n° 4 (December 2020)  

Public [article]  inGeo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 275 - 292 Titre : Social media as passive geo-participation in transportation planning – how effective are topic modeling & sentiment analysis in comparison with citizen surveys? Type de document : Article/Communication Auteurs : Oliver Lock, Auteur ; Chris Pettit, Auteur Année de publication : 2020 Article en page(s) : pp 275 - 292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] artefact [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données localisées des bénévoles [Termes IGN] données massives [Termes IGN] planification urbaine [Termes IGN] réseau social [Termes IGN] sentiment [Termes IGN] Sydney (Nouvelle-Galles du Sud) [Termes IGN] traitement du langage naturel [Termes IGN] transport public [Termes IGN] ville intelligente Résumé : (auteur) We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion. Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city. With such pressures on existing public transportation systems, this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services. This research forms a case study of the use of passively collected forms of big data in cities – focusing on Sydney, Australia. Firstly, it examines social media data (Tweets) related to public transport performance. Secondly, it joins this to longitudinal big data – delay information continuously broadcast by the network over a year, thus forming hundreds of millions of data artifacts. Topics, tones, and sentiment are modeled using machine learning and Natural Language Processing (NLP) techniques. These resulting data, and models, are compared to opinions derived from a citizen survey among users. The validity of such data and models versus the intentions of users, in the context of systems that monitor and improve transport performance, are discussed. As such, key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques. Numéro de notice : A2020-787 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1815596 Date de publication en ligne : 21/09/2020 En ligne : https://doi.org/10.1080/10095020.2020.1815596 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96545 [article]

A deep learning architecture for semantic address matching / Yue Lin in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

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A framework for extracting urban functional regions based on multiprototype word embeddings using points-of-interest data / Sheng Hu in Computers, Environment and Urban Systems, vol 80 (March 2020)  

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Comparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)  

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Extraction de connaissances pour la description de l'environnement maritime côtier à partir de textes d'aide à la navigation / Léa Lamotte in Revue des Nouvelles Technologies de l'Information, E.36 (2020)

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Representation learning for natural language processing / Zhiyuan Liu (2020)  

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Mapping urban fingerprints of odonyms automatically extracted from French novels / Ludovic Moncla in International journal of geographical information science IJGIS, vol 33 n° 12 (December 2019)  

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A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements / Yingjie Hu in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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GeoTxt: A scalable geoparsing system for unstructured text geolocation / Morteza Karimzadeh in Transactions in GIS, vol 23 n° 1 (February 2019)  

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Valorisation de récits de vie de Républicains espagnols / Catherine Dominguès (2019) 

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Fictive motion extraction and classification / Ekaterina Egorova in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)  

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