Academic Articles & Research Papers

Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies

Online platforms have become the primary means for travellers to search, compare, and book accommodations for their trips. Consequently, online platforms and revenue managers must acquire a comprehensive comprehension of these dynamics to f...

An Overview of Empirical Natural Language Processing

In recent years, there has been a resurgence in research on empirical methods in natural language processing. These methods employ learning techniques to automatically extract linguistic knowledge from natural language corpora rather than r...

Natural language processing

Abstract Natural language processing has two primary roles to play in the storage and retrieval of large bodies of information: providing a friendly, easily‐learned interface to information retrieval systems, and automatically structuring t...

Natural language processing in information retrieval

The role and contributions of natural-language processing in information-retrieval and artificial-intelligence research is examined in the context of large operational information-retrieval systems and services. State-of-the-art information...

Natural Language Processing

In most natural language processing applications, Description Logics have been used to encode in a knowledge base some syntactic, semantic, and pragmatic elements needed to drive the semantic interpretation and the natural language generati...

Digital and artificial intelligence-assisted medication management for older adults with chronic diseases: a systematic review and meta-analysis of randomized controlled trials.

Decolonizing Algorithms: AI-Driven Media and the Reclamation of African Linguistic Identities

This study examines the influence of artificial intelligence (AI)-driven media platforms on South Africa's indigenous languages—Setswana, Tshivenda, and Xitsonga—in the country's diverse linguistic environment. It examines how algorithmic b...

Provable Limitations of Acquiring Meaning from Ungrounded Form: What Will Future Language Models Understand?

AbstractLanguage models trained on billions of tokens have recently led to unprecedented results on many NLP tasks. This success raises the question of whether, in principle, a system can ever “understand” raw text without access to some fo...

Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed

BackgroundNatural language processing (NLP) is an important traditional field in computer science, but its application in medical research has faced many challenges. With the extensive digitalization of medical information globally and incr...

Training‐Efficient Personalised Knee Joint Moment Estimation via an Incremental Broad Learning System

ABSTRACT Knee joint moment estimation is a critical component in biomechanical analysis, with profound implications for rehabilitation assessment and the development of assistive devices like exoskeletons. However, existing data‐driven appr...

Location factors and ecosystem embedding of sustainability-engaged blockchain companies in the US. A web-based analysis

While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy ...

Deep learning-based personalized learning path recommendation system for higher education

Abstract The growing variety of student profiles in higher education has made it more important than ever to have smart systems that can change learning experiences on the job. Current recommendation algorithms fail to capture the complex r...

MedScan, a natural language processing engine for MEDLINE abstracts

MOTIVATION: The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely us...

Machine Learning and Natural Language Processing in Mental Health: Systematic Review

BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...

A Systematic Review of the Relationship Between Maltreatment and Mentalization in Middle Childhood.

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

L’IGF A L’EPREUVE DU CONTROLE SYSTEMIQUE ET DE LA DIGITALISATION : MUTATIONS DU CONTROLE FINANCIER PUBLIC EN RDC (2020-2027)

Résumé : Cette étude analyse la transformation de l’Inspection Générale des Finances (IGF) de la RDC à travers les réformes de 2020-2023 et l’annonce de son plan stratégique 2025-2027 articulant contrôle systémique et digitalisation. A part...

Information Extraction From FDA Drug Labeling to Enhance Product-Specific Guidance Assessment Using Natural Language Processing

Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and ...

Machine Reading Comprehension for the Tamil Language With Translated SQuAD

Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...

Research on application of GPS-based wireless communication system in highway landslide

Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and indus...