research paper natural language processing

Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... Browse SoTA > Natural Language Processing Natural Language Processing. 2339 benchmarks • 668 tasks • 2018 datasets • 28014 papers with code Representation Learning Representation Learning. 16 benchmarks 3672 papers with ...

Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP ...

The field of Natural Language Processing (NLP) has evolved with, and as well as influenced, recent advances in Artificial Intelligence (AI) and computing technologies, opening up new applications and novel interactions with humans. ... NLPJ publishes research papers, review (survey) articles, position papers, tutorial and best practice papers ...

The Open Access Natural Language Processing Journal aims to advance modern understanding and practice of trustworthy, interpretable, explainable human-centered and hybrid Artificial Intelligence as it relates to all aspects of human language. ... The NLP journal welcomes original research papers, review papers, position papers, tutorial and ...

Natural Language Processing can be applied into various areas like Ma chine Translation, Email Spam detection, Information Extraction, Summarization, Question Answering etc. 6.1 Machine ...

A. Brief Overview of Natural Language Processing (NLP) Natural Language Processing (NLP) is a multidisciplinary field that focuses on enabling. machines to understand, interpret, and generate ...

Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources include data, time, storage, or energy, all of which are naturally limited and unevenly distributed. This motivates research into efficient methods that require ...

Computational linguistics, also known as natural language processing (NLP), is the subfield of computer science concerned with using computational techniques to learn, understand, and produce human language content. Computational linguistic systems can have multiple purposes: The goal can be aiding human-human communication, such as in machine ...

As an efficient approach to understand, generate, and process natural language texts, research in natural language processing (NLP) has exhibited a rapid spread and wide adoption in recent years. Given the increasing research work in this area, several NLP-related approaches have been surveyed in the research community. However, a comprehensive study that categorizes established topics ...

Over the last decade, deep learning has revolutionized machine learning. Neural network architectures have become the method of choice for many different applications; in this paper, we survey the applications of deep learning to natural language processing (NLP) problems. We begin by briefly reviewing the basic notions and major architectures of deep learning, including some recent advances ...

Natural Language Processing (NLP) is witnessing a remarkable breakthrough driven by the success of Large Language Models (LLMs). LLMs have gained significant attention across academia and industry for their versatile applications in text generation, question answering, and text summarization. As the landscape of NLP evolves with an increasing number of domain-specific LLMs employing diverse ...

Dhiraj Jadhav. Department of Data Science &. Artificial Intelligence. Bournemouth University. [email protected]. Abstract — This research paper explores recent. advancements in Natural ...

Performing groundbreaking Natural Language Processing research since 1999.

Natural Language Processing (NLP) research at Google focuses on algorithms that apply at scale, across languages, and across domains. Our systems are used in numerous ways across Google, impacting user experience in search, mobile, apps, ads, translate and more. ... In this paper, we propose a novel method to automatically revise prompts for ...

As an essential part of artificial intelligence technology, natural language processing is rooted in multiple disciplines such as linguistics, computer science, and mathematics. The rapid advancements in natural language processing provides strong support for machine translation research. This paper first introduces the key concepts and main content of natural language processing, and briefly ...

Hindi Language. Image captioning refers to the process of generating a textual description that describes objects and activities present in a given image. It connects two fields of artificial intelligence, computer vision, and natural language processing. Computer vision and natural language processing deal with image understanding and language ...

A natural language processing system that links medical terms in electronic health record notes to lay definitions: System development using physician reviews. Journal of Medical Internet Research , 20, e26. doi:10.2196/jmir.8669

Natural language processing (NLP) is gaining momentum in management research for its ability to automatically analyze and comprehend human language. Yet, despite its extensive application in management research, there is neither a comprehensive review of extant literature on such applications, nor is there a detailed walkthrough on how it can ...

Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish ...

Abstract: Processing natural language such as English has always been one of the central research issues of artificial intelligence, both because of the key role language plays in human intelligence and because of the wealth of potential applications. Many of the knowledge representation and inference techniques that have been applied successfully in knowledge-based systems were originally ...

The normal language preparing communicates its interest through a tremendous wide range of utilizations. Already, NLP used to manage static data. Nowadays, NLP is doing impressively with the corpus, lexicon database, and pattern reorganization. These incorporate framework of communicated in language that coordinate discourse and regular language.

Natural language processing is an integral area of computer. science in which machine learni ng and computational. linguistics are b roadly used. This field is mainly concerned. with making t he h ...

Large language models (LLMs) have shown remarkable performance in various natural language processing tasks. However, a primary constraint they face is the context limit, i.e., the maximum number of tokens they can process. Previous works have explored architectural changes and modifications in positional encoding to relax the constraint, but they often require expensive training or do not ...

These tools are now indispensable in the biological research landscape, bridging the gap between the vastness of unannotated sequences and meaningful biological insights. Results. In this work, we propose a novel pipeline for KEGG orthology annotation of bacterial protein sequences that uses natural language processing and deep learning.

This paper presents a proof of concept for a search engine tailored to geospatial services in Switzerland. It addresses challenges such as scraping data from various OGC web service providers, enhancing metadata quality through Natural Language Processing, and optimizing search functionality and ranking methods.

Natural language processing (NLP) is a research domain exploring how computers can be used to interpret and manipulate natural language text or speech [68]. With the advance of machine learning ...

Matthias Winkenbach, director of research for the MIT Center for Transportation and Logistics, uses machine learning, specifically a transformer model from natural language processing, to make vehicle routing more efficient and adaptable for unexpected events.

As the rapidly advancing domain of natural language processing (NLP), large language models (LLMs) have emerged as powerful tools for interpreting human commands and generating text across various tasks. Nonetheless, the resilience of LLMs to handle text containing inherent errors, stemming from human interactions and collaborative systems, has not been thoroughly explored. Our study ...

The paper also addresses the challenges and opportunities in SA, such as dealing with sarcasm and irony, analyzing multi-lingual data, and addressing ethical concerns. ... Keywords: Sentiment Analysis, Natural Language Processing Mining, Emotion Classification, Ethical Considerations I. ... With research concentrating on feature selection ...

The evaluation of performance using competencies within a structured framework holds significant importance across various professional domains, particularly in roles like project manager. Typically, this assessment process, overseen by senior evaluators, involves scoring competencies based on data gathered from interviews, completed forms, and evaluation programs. However, this task is ...