Top Research Papers on NLP

Applications of NLP include a number of fields of studies, such as machine translation, natural language text processing and summarization, user interfaces, multilingual and cross language information retrieval, speech recognition, artificial intelligence and expert systems.

The outcome showed that the largest number of NLP publications occurred in 2021, with the first publication being in 1989, and the leading journal with the most publications was IEEE Access, and NLP papers have earned the most citations than any other journal.

The goal of the Natural Language Processing is to style and build software system which will analyze, understand, and generate languages that humans use naturally, so as that you just could also be ready to address your computer as if you were addressing another person.

This paper delves into the application of Natural Language Processing techniques in recommendation systems, specifically focusing on novel approaches to enhance recommendation accuracy and user satisfaction, and introduces a novel recommendation method termed "Knowledge Graph Embedding for Contextual Recommendation".

This paper focuses on the semantic networks of lexical information, in order to highlight their value but also the urgent need to design and implement an electronic conceptual dictionary with ontological structure for the modern Greek language, according to international dictionary standards.

NLP has a lot of potential for producing computer interfaces that are easier to use for humans, because people will be able to communicate with computers in their own language rather than having to learn a computer language.

Overall, this study demonstrates the transformative potential of NLP in optimizing the resume screening process by providing a scalable, efficient, and unbiased solution for large organizations.

Evidence of lexical, syntactic, and semantic ambiguities that complicate the language understanding process is presented and focus on way ethical concerns like bias are paramount in making current NLP systems neutral is brought.

It is found that duplicate tasks share conceptual information and are rather created by inexperienced developers, so by tuning different features to predict development tasks with a gradient or a Fidelity loss function a system can identify a duplicate tasks with 100% accuracy.

Opportunities that Natural Language Processing (NLP) are providing to insurance are explained and different methods used today in practice traces back the story of them are details.

This book represents a suitable point of departure for conventions in ANLP and provides current researchers with some guidelines from which to begin, some framework within which to work, and some goals for which …

The purpose of this research will be carried out development of a chatbot application for information about the corporate, making it easier for visitors to find the information needed, with a Natural Language Processing approach.

A survey on Natural language processing (NLP) and its approaches is presented and it is shown that NLP uses Artificial Intelligence, and is used to recover information in data mining.

The proposed system explores to classify the shared posts in to positive, negative comments, identifies particular user who have commented on the negative side on the online social networking specifically on the facebook and also handles the web filtering technique to filter pornography websites.

The study identifies the publication trends, influential journals, cited articles, influential authors, institutions, countries, key research areas, and research clusters in the NLP field and revealed that the first NLP publication was in 1989, with the highest publication recorded in 2021.

NLP and statistics-based “machine learning” (ML) have demonstrated accomplishment in challenging learning challenges and Automation, self-management technologies, speech synthesis, and deep learning advancements have empowered machines to achieve heretofore unthinkable feats.

It is suggested that considering a biomedical QA task is not necessarily such a simplification over open-domain QA as represented in the recent TREC evaluations.

A review is presented on the latest concepts in the field of word processing, information extraction, and implementing an interface for text analysis using the C++ programming language and Visual Studio 2015 edition.

TF-IDF, Cosine Similarity NLP techniques were employed by the authors to match strings in the suggested system, and output results are obtained instantly in real time.

Natural language processing (NLP), which makes automated systems and customers interact more naturally and human-like, is a crucial component of chatbot-based customer service. Thanks to this technology, chatbots can now hear and comprehend speech or words quite similar to how humans do, providing efficient and customized customer support. NLPenabled chatbots can do tasks including answering questions, troubleshooting, and enhancing customer happiness. Aspects of natural language processing that are essential include sentiment analysis, entity extraction, and intent detection. NLP-driven chatb...

This study explores the current standing of NLP in aviation from the perspective of both research and industry, and identifies safety reports analyses, aviation maintenance, and air traffic control as the three main focus areas of N LP research in aviation.

This book represents a suitable point of departure for conventions in ANLP and provides current researchers with some guidelines from which to begin, some framework within which to work, and some goals for which …

Analyzing demographic data in tandem with cyberbullying experiences found a clear correlation between social media use length and the likelihood of running into cyberbullying, and suggests the creation of a customized natural language processing system specifically designed to identify Thai language cyberbullying events.

The discussion in this paper shows that natural language processing helps computers communicate with humans in their own language and makes scaling other language-related tasks easier and more systematic.

This research presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and cataloging individual words in a language.

This article introduces archivists to NLP with a presentation of the NLP Continuum and a description of the Archives Axiom and concludes that while NLP offers advantages for indexing and accessing electronic archives, its incapacity to understand records and recordkeeping systems results in serious limitations for archival operations.

The goal is to train and tune NLP models to help speed up the screening, ranking, and matching of job candidates using resumes and job descriptions to address the recruitment efficiency, candidate fit and engagement challenges.

Innovation is needed in developing more energy-efficient models, strategies to mitigate bias, and stricter data protection policies, so that AI-driven NLP can provide broader benefits to society across various domains.

This research aims to automate the process of using the Meta Model in conversation in order to eliminate human errors, thereby increasing the efficiency and accuracy of this method.

The need of applying NLP technologies in the field of e-governance is shown and the issues, which can be resolved very easily with the help of these modern technologies are focused on.

The app's innovative approach to storytelling provides a tailored experience that allows hearing-impaired children to enjoy stories in a way that is engaging and accessible, and its contribution to the field of assistive technology is significant.

This comparative study aims to analyze and compare the performance, language support, community support and ease of use of many popular Python libraries for NLP like NLTK, spaCy, TextBlob, Flair, Jina, Gensim etc.

A study of extractive and abstract methods for summarizing texts has been made and this paper analyses above mentioned methods which yields a less repetitive and a more concentrated summary.

The end to end working of a python application which efficiently screens the resumes of the candidates based on the organization's requirement is explained.

This project enables physically challenged people to code without using a keyboard and can code entirely by their voice and execute their code using Natural Language Processing (NLP).

Les orientations actuelles de the recherche sur le langage naturel sont : le data mining and l'extraction d'entite, l'amelioration du filtrage (techniques d'alerte), the Recherche translinguistique, the vitesse, le resume automatique, l-indexation assistee par ordinateur.

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The research is centered on some of the important issues that arise using it in natural language processing and the interpretation capabilities of a language understanding system depending on the semantic theory is not sufficient in all aspects.

Natural Language Processing (NLP) has experienced essential transformations thanks to machine learning (ML) technical implementations. This research discusses the integrated nature of NLP and ML through data driven methodologies that led to radical evolution in text classification and sentiment analysis and machine translation and question-answering systems. Deep learning architectures, particularly transformers like BERT, GPT, and T5, which utilize extensive datasets and contextual embeddings, have largely replaced traditional rule-based methods. This study examines crucial ML approaches, suc...

There exists a contextual and methodological gap relating to Natural Language Processing (NLP) for sentiment analysis in social media, pointing towards future directions in hybrid NLP models for improved sentiment analysis across different languages and cultural contexts.

An MMS method combining the techniques of natural language processing, speech processing, computer vision and advanced encryption standard (AES) encryption is used to explore the rich information contained in multi-modal data to improve the quality and security.

NLP adalah cabang dari kecerdasan buatan (AI) yang berhubungan dengan melatih komputer untuk memahami, memproses, dan menghasilkan bahasa. Salah satu implementasi NLP yang sangat penting adalah penerapannya di dunia pendidikan. NLP adalah proses yang efektif untuk membantu siswa dalam proses pembelajaran. Menerapkan NLP dalam lingkungan pendidikan tidak hanya membantu dalam mengembangkan proses bahasa yang efektif, tetapi juga penting untuk meningkatkan prestasi akademik. Beberapa penerapan NLP di dunia pendidikan adalah Peringkasan Teks dan Paraphrasing, Tanya Jawab, Chatbot (feedback dari pe...

The method of creating a voice assistant without using cloud services is described, which will allow the expansion of such devices in the future.

A novel approach that makes use of various machine learning, natural language processing, and tools like WorldNet, Word2vec, word mover's distance, cosine similarity, Multinomial Naive Bayes (MNB), and term frequency-inverse document frequency (TF-IDF) is proposed.

This paper investigates how learning environments that are customized to the requirements of individual students can be created using natural language processing (NLP), and how it impacts English language training (ELT).

Pengembangan actor virtual dalam banyak aplikasi, dari sebuah tampilan untuk pengguna (user interface) sampai computer entertaintment menciptakan ekspektasi terhadap kemampuan actor virtual tersebut dalam hal memahami bahasa natural.

This report implements a NLP machine learning with TensorFlow, an end-to-end open source plataform for machine learning applications, to process and classify evenct based on files containing only text.

This paper is focusing on three NLP tools Core NLP, Apertium and PRAAT and using them on single ambiguous sentence.

This Doctoral Consortium paper discusses how NLP can be applied in the domain of BPM in order to automatically generate business process models from existing documentation within the organization.

The research and development work preceding the piloting of precisely such a tool, capable not only of identifying the typical errors in L2 student writing, but also of making adequate corrections, is described.