Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing-Reference-Cited by-同舟云学术

Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing

Published:2019-03-05 Issue:2 Volume:20 Page:175-193
ISSN:1612-4782
Container-title:Cognitive Processing
language:en
Short-container-title:Cogn Process

Author:

Amirhosseini Mohammad Hossein^ORCID,Kazemian Hassan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Cognitive Neuroscience,Experimental and Cognitive Psychology,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s10339-019-00912-3.pdf

Reference32 articles.

1. ANLP (2016) Improving your communication using Manteya Email. https://anlp.org/business-resources-for-nlp-professionals/manteya-email . Accessed 18 Dec 2017

2. Bensted C (2014) Representational systems. http://badis.co.uk/resources/Repsys.pdf . Accessed 12 Feb 2018

3. Bird S, Klein E, Loper E (2009) Natural Language Processing with python: analyzing text with the natural language toolkit. O’Reilly Media Inc, Newton

4. Brefi Group Limited (2004) Representational system. http://www.brefigroup.co.uk/acrobat/nlp_representational_systems.pdf . Accessed 24 Feb 2018

5. Casale P (2012) NLP secrets: upgrade your mind with Neuro Linguistic Programming. Creative Media NZ Ltd, Auckland

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Detection of Fake News Using Machine Intelligence for Societal Benefit;Lecture Notes in Networks and Systems;2024

2. A New Method for Graph-Based Representation of Text in Natural Language Processing;Electronics;2023-06-27

3. Knowledge graphs to an analysis and visualization of texts from scientific articles;Procedia Computer Science;2023

4. Programa de Treinamento em Voz e Comunicação Melhora o Desempenho de Universitários em Apresentações Orais;CoDAS;2023

5. Voice and Communication Training Program Improves Performance of University Students in Oral Presentations;CoDAS;2023