An end-user pipeline for scrapping and visualizing semi-structured data over the Web
- Autores
- Bosetti, Gabriela Alejandra; Firmenich, Sergio Damián; Winckler, Marco; Rossi, Gustavo Héctor; Cornejo Fandos, Ulises Jeremías; Egyed-Zsigmond, Elöd
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets.
Publicado en Lecture Notes in Computer Science book series (LNCS, vol. 11496)
Laboratorio de Investigación y Formación en Informática Avanzada - Materia
-
Ciencias Informáticas
Infovis
Web augmentation
Web scrapping - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/119026
Ver los metadatos del registro completo
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An end-user pipeline for scrapping and visualizing semi-structured data over the WebBosetti, Gabriela AlejandraFirmenich, Sergio DamiánWinckler, MarcoRossi, Gustavo HéctorCornejo Fandos, Ulises JeremíasEgyed-Zsigmond, ElödCiencias InformáticasInfovisWeb augmentationWeb scrappingThe Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets.Publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 11496)Laboratorio de Investigación y Formación en Informática Avanzada2019info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf223-237http://sedici.unlp.edu.ar/handle/10915/119026enginfo:eu-repo/semantics/altIdentifier/isbn/978-3-030-19274-7info:eu-repo/semantics/altIdentifier/issn/0302-9743info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-030-19274-7_17info:eu-repo/semantics/altIdentifier/hdl/11746/10709info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:28:04Zoai:sedici.unlp.edu.ar:10915/119026Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:28:04.838SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
spellingShingle |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web Bosetti, Gabriela Alejandra Ciencias Informáticas Infovis Web augmentation Web scrapping |
title_short |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_full |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_fullStr |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_full_unstemmed |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
title_sort |
An end-user pipeline for scrapping and visualizing semi-structured data over the Web |
dc.creator.none.fl_str_mv |
Bosetti, Gabriela Alejandra Firmenich, Sergio Damián Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Jeremías Egyed-Zsigmond, Elöd |
author |
Bosetti, Gabriela Alejandra |
author_facet |
Bosetti, Gabriela Alejandra Firmenich, Sergio Damián Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Jeremías Egyed-Zsigmond, Elöd |
author_role |
author |
author2 |
Firmenich, Sergio Damián Winckler, Marco Rossi, Gustavo Héctor Cornejo Fandos, Ulises Jeremías Egyed-Zsigmond, Elöd |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Infovis Web augmentation Web scrapping |
topic |
Ciencias Informáticas Infovis Web augmentation Web scrapping |
dc.description.none.fl_txt_mv |
The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets. Publicado en <i>Lecture Notes in Computer Science</i> book series (LNCS, vol. 11496) Laboratorio de Investigación y Formación en Informática Avanzada |
description |
The Web is a vast source of semi-structured data sets that are made readily available to support the construction of new knowledge. Information visualization techniques have been demonstrated a suitable alternative for allowing users to analyze and understand a large amount of data. However, the steps required for visualizing semi-structured data obtained from the Web is not straightforward, and it requires proper treatment before information visualization techniques could be applied. In this work, we present a visualization pipeline for describing the fundamental operations required for visualizing semi-structured data over the Web. For that, we employ Web Scrapping and Web Augmentation techniques for supporting interactive visualizations and solving tasks without changing the context of use of the data. Our approach is duly supported by a framework including scrapping, augmenting and visualization tools and it has been applied to different kinds of websites to demonstrate its validity and feasibility. Our ultimate goal is to expand the limits of our technology for improving the user interaction with websites and creating new experiences for better understanding large data sets. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 |
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eng |
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