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A Neural NLP Framework for an Optimized UI for Creating Tenders in the TED Database of the EU

Authors:
Sangramsing N Kayte
Peter Schneider-Kamp

Keywords: Natural Language Processing, Natural Language Understanding, Natural User Interfaces, Named-Entity Recognition, Logistic Regression, European Union, Tender Electronic Daily, Common Procurement Vocabulary.

Abstract:
The developments in the fields of web technologies, digital libraries, technical documentation, and medical data have made it easier to access a larger amount of textual documents, which can be combined to develop useful data resources. Text mining or the knowledge discovery from textual databases is a challenging task, in particular when having to meet the standards of the depth of natural language that is employed by most of the available documents. The primary goal of this research is to investigate how Machine Learning algorithms techniques can be applied for text mining in the context of creating an optimized user interface for tender creation in the Tender Electronic Daily database used for public procurement throughout the European Union (EU). This paper explains the scope and concept of Natural Language Processing (NLP) for such text mining projects. We also present a detailed overview of the different techniques involved in Natural Language Processing and Understanding along with the related work.

Pages: 19 to 24

Copyright: Copyright (c) IARIA, 2019

Publication date: September 22, 2019

Published in: conference

ISSN: 2326-9324

ISBN: 978-1-61208-739-9

Location: Porto, Portugal

Dates: from September 22, 2019 to September 26, 2019