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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: ZENODO
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
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Multi-layout Invoice Document Dataset (MIDD)

Authors: Baviskar, Dipali; Ahirrao, Swati; Kotecha, Ketan;

Multi-layout Invoice Document Dataset (MIDD)

Abstract

Research Purpose/Goal of Multi-Layout Invoice Document Dataset (MIDD) · To provide the annotated and varied invoice layout documents in IOB format to identify and extract named entities (named entity recognition) from the invoice documents to the researchers working in this domain. Obtaining a high-quality and sufficient annotated corpus for automated information extraction from unstructured documents is the biggest challenge researchers face. · To overcome the limitations of rule-based and template-based named entity extraction from unstructured documents traditionally used so far in information extraction approaches. Template-free processing is the only key to processing, and managing a huge pile of unstructured documents in the recent digitized era. · To provide varied invoice layouts so that researchers can develop a generalized AI-based model that will train on various unstructured invoice layouts. Obtained structured output can later be utilized for integrating into information management application of the organization and used for the decision-making process.

Pune

Keywords

Artificial Intelligence (AI); information extraction; Named Entity Recognition (NER); unstructured data; template-free processing

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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409