Lexical Challenges in the Intersection of Applied Linguistics and ANLP

2012 ◽  
pp. 50-72 ◽  
Author(s):  
Scott Jarvis
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Language Use ◽  
Applied Linguistics ◽  
Lexical Diversity ◽  
Language Knowledge

The investigation of natural language processing in the field of Applied Linguistics is pursued with both theoretical and practical aims, such as arriving at a clearer understanding of the nature of language knowledge, the rules that govern its use, how it is acquired, how unique it is to individual speakers, and how it can best be taught to learners. The purpose of this chapter is to draw attention to some of the prominent areas of overlap between Applied Linguistics and ANLP, highlighting the problems they face in relation to the characterization of lexical deployment, and focusing particularly on challenges related to the measurement of lexical diversity and the representation of the unique lexical signatures of individual samples of natural language use. The bulk of the chapter is devoted to describing preliminary solutions to these challenges.

scholarly journals Does higher education properly prepare graduates for the growing artificial intelligence market? Gaps identification using text mining

2021 ◽  
pp. 1-13
Author(s):  
Lamiae Benhayoun ◽  
Daniel Lang
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Academic Training ◽  
Market Requirements ◽  
Job Advertisements ◽  
The Individual

BACKGROUND: The renewed advent of Artificial Intelligence (AI) is inducing profound changes in the classic categories of technology professions and is creating the need for new specific skills. OBJECTIVE: Identify the gaps in terms of skills between academic training on AI in French engineering and Business Schools, and the requirements of the labour market. METHOD: Extraction of AI training contents from the schools’ websites and scraping of a job advertisements’ website. Then, analysis based on a text mining approach with a Python code for Natural Language Processing. RESULTS: Categorization of occupations related to AI. Characterization of three classes of skills for the AI market: Technical, Soft and Interdisciplinary. Skills’ gaps concern some professional certifications and the mastery of specific tools, research abilities, and awareness of ethical and regulatory dimensions of AI. CONCLUSIONS: A deep analysis using algorithms for Natural Language Processing. Results that provide a better understanding of the AI capability components at the individual and the organizational levels. A study that can help shape educational programs to respond to the AI market requirements.

scholarly journals Bibliometric and Geographical Analysis of Cell Death Related Literature

2015 ◽  
Author(s):  
Vijaykumar Yogesh Muley ◽  
Anne Hahn ◽  
Pravin Paikrao
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Scientific Community ◽  
Official Language ◽  
Lexical Diversity ◽  
Part Of Speech Tagging ◽  
Part Of Speech ◽  
Recent Developments ◽  
Speech Tagging

Natural language processing continues to gain importance in a thriving scientific community that communicates its latest results in such a frequency that following up on the most recent developments even in a specific field cannot be managed by human readers alone. Here we summarize and compare the publishing activity of the previous years on a distinct topic across several countries, addressing not only publishing frequency and history, but also stylistic characteristics that are accessible by means of natural language processing. Though there are no profound differences in the sentence lengths or lexical diversity among different countries, writing styles approached by Part-Of-Speech tagging are similar among countries that share history or official language or those are spatially close.

scholarly journals Characterization of patients with advanced chronic pancreatitis using natural language processing of radiology reports

PLoS ONE ◽  
2020 ◽  
Vol 15 (8) ◽  
pp. e0236817
Author(s):  
Fagen Xie ◽  
Qiaoling Chen ◽  
Yichen Zhou ◽  
Wansu Chen ◽  
Jemianne Bautista ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Chronic Pancreatitis ◽  
Natural Language ◽  
Language Processing ◽  
Radiology Reports

scholarly journals An interactive dashboard to track themes, development maturity, and global equity in clinical artificial intelligence research

2021 ◽  
Author(s):  
Joe Zhang ◽  
Stephen Whebell ◽  
Jack Gallifant ◽  
Sanjay Budhdeo ◽  
Heather Mattie ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Natural Language Processing ◽  
Natural Language ◽  
Real Time ◽  
Language Processing ◽  
Artificial Intelligence Research ◽  
End To End ◽  
Monitoring Progress

The global clinical artificial intelligence (AI) research landscape is constantly evolving, with heterogeneity across specialties, disease areas, geographical representation, and development maturity. Continual assessment of this landscape is important for monitoring progress. Taking advantage of developments in natural language processing (NLP), we produce an end-to-end NLP pipeline to automate classification and characterization of all original clinical AI research on MEDLINE, outputting real-time results to a public, interactive dashboard (https://aiforhealth.app/).

Variations in terminology

Terminology ◽  
2010 ◽  
Vol 16 (1) ◽  
pp. 30-50 ◽  
Author(s):  
Anne Condamines
Keyword(s):  
Risk Management ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Language Use ◽  
Knowledge Engineering ◽  
Field Of Study ◽  
New Approach ◽  
Individual Variations ◽  
Definition Of

The study of variation in terminology came to the fore over the last fifteen years in connection with advances in textual terminology. This new approach to terminology could be a way of improving the management of risk related to language use in the workplace and to contribute to the definition of a “linguistics of the workplace”. As a theoretical field of study, linguistics has hardly found any application in the workplace. Two of its applied branches, however, Sociolinguistics and Natural Language Processing (NLP) are relevant. Both deal with lexical phenomena, — i.e. terminology — sociolinguistics taking into account very subtle inter-individual variations and NLP being more interested in stability in the use. So, taking into account variations in building terminologies could be a means of considering both description and prescription, use and norm. This approach to terminology, which has been made possible thanks to NLP and Knowledge Engineering could be a way of meeting needs in the workplace concerning risk management related to language use.

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