CYAICLDBLGSep 4, 2020

Data Readiness for Natural Language Processing

arXiv:2009.02043v22 citations
Originality Synthesis-oriented
AI Analysis

It tackles data preparation issues for organizations using NLP in business processes, but it is incremental as it builds on existing practices.

The paper addresses data readiness challenges in NLP by providing a framework for organizations to identify, validate, and prepare data to facilitate automated analysis, based on practical experiences from applied research.

This document concerns data readiness in the context of machine learning and Natural Language Processing. It describes how an organization may proceed to identify, make available, validate, and prepare data to facilitate automated analysis methods. The contents of the document is based on the practical challenges and frequently asked questions we have encountered in our work as an applied research institute with helping organizations and companies, both in the public and private sectors, to use data in their business processes.

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Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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