To systematically evaluate the effectiveness and methodologic approaches of natural language processing (NLP) techniques for early detection of cognitive decline through speech and language analysis. We conducted a comprehensive search of 8 databases from inception through August 31, 2024, following ...
Natural Language Processing (NLP) is a subfield of artificial intelligence that focuses on the interaction between computers and humans using natural language. In recent years, NLP techniques have made significant advancements in various applications such as sentiment analysis, chatbots, machine translation...
Name Entity Recognition (NER) is the most primitive algorithm in the field of NLP. The process extracts the core ‘entities’ present in the text. These entities represent the fundamental themes in the text. Entities could be the names of people, names of companies, dates, monetary values, q...
Over the last decades, multiple developments in the field of natural language processing (NLP) have resulted in achieving large language models (LLMs).To understand LLMs, let's first explore the statistical techniques for NLP that over time have contributed to the current techniques....
Natural language processing turns text and audio speech into encoded, structured data based on a given framework. It’s one of the fastest-evolving branches of artificial intelligence, drawing from a range of disciplines, such as data science and computational linguistics, to help computers understand...
Tokenizer is very first and very important part of any Language processing. Because when you receive lot of text then the first step to extract information from that bunch of text is to tear apart big bunch of text into some shorter tokens, that represents some useful part of the speech. ...
In this section, we introduce some successful deep learning algorithms for natural language processing. With the rapid growth of deep learning, many recent studies expect to build low-dimensional, dense, and real-valued vector as text features for opinion mining without any feature engineering. The...
Constructing Financial Sentimental Factors in Chinese Market Using Techniques of Natural Language Processing - Coldog2333/Financial-NLP
Natural Language ProcessingDecision Model and Notation (DMN) has become a relevant topic for organizations since it allows users to control their processes and organizational decisions. The increasing use of DMN decision tables to capture critical business knowledge raises the need for supporting analysis...
To provide a critical appraisal and synthesis of evidence concerning the application of natural language processing (NLP) techniques for clinical purposes in the geriatric population. In particular, we discuss the state of the art on studying language in healthy and pathological ageing, focusing on th...