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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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Relations from Italian Wikipedia using Unsupervised Information Extraction

Authors: Pierpaolo Basile; Lucia Siciliani; Pierluigi Cassotti; Marco de Gemmis; Pasquale Lops;

Relations from Italian Wikipedia using Unsupervised Information Extraction

Abstract

This dataset contains relations extracted from the Italian Wikipedia by the WikiOIE framework. WikiOIE is based on UDPipe and the Universal Dependencies project for text processing. It easily allows customizing the information extraction (IE) approach to automatically extract triples (subject, predicate, object). This dataset contains relations extracted by two unsupervised IE methods. The former (simple) is based only on PoS-tag patterns; the latter (simpledep) also uses syntactic dependencies. The extraction process is provided in JSON format. More information and the Java code are available here https://github.com/pippokill/WikiOIE Pierluigi Cassotti, Lucia Siciliani, Pierpaolo Basile,Marco de Gemmis, and Pasquale Lops. 2021. Extracting relations from Italian Wikipedia using unsupervised information extraction. In Proceedings of the 11th Italian Information Retrieval Workshop 2021 (IIR 2021). CEUR-WS.

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Keywords

Open Information Extraction, Information Retrieval, Universal Dependencies, Natural Language Processing, Wikipedia

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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