Academic Articles & Research Papers

Python Natural Language Processing

Leverage the power of machine learning and deep learning to extract information from text dataAbout This BookImplement Machine Learning and Deep Learning techniques for efficient natural language processingGet started with NLTK and implemen...

Construction of a knowledge graph for the educational statistical indicator system based on large language models

Current statistical work in the field of educational development faces challenges such as low knowledge-retrieval efficiency and high technical barriers to data utilization. This study focuses on the knowledge related to the indicator syste...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. Th...

Assessing perception and equity of cultural ecosystem services in urban parks using social media data

Abstract Scientific assessment of cultural ecosystem services (CESs) levels in urban parks and refined analysis of their spatial equity are essential for residents’ social well-being. However, traditional assessment methods often fail to ca...

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

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...

Distributional Memory: A General Framework for Corpus-Based Semantics

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...

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...

Lexical Functions in Lexicography and Natural Language Processing

Lexical Functions in Lexicography and Natural Language Processing is entirely devoted to the topic of Lexical Functions, which have been introduced in the framework of the Meaning-Text Theory (MTT) as a means for describing restricted lexic...

Natural language processing in-and-for design research

Abstract We review the scholarly contributions that utilise natural language processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period...

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...

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA

Abstract BackgroundThe quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender in...

BERT applications in natural language processing: a review

BERT (Bidirectional Encoder Representations from Transformers) has revolutionized Natural Language Processing (NLP) by significantly enhancing the capabilities of language models. This review study examines the complex nature of BERT, inclu...

On the Explainability of Natural Language Processing Deep Models

Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...

Different hybrid machine intelligence techniques for handling IoT‐based imbalanced data

Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...

Long-Acting Nanomedicine for Tuberculosis: A Mechanism-Informed Framework.

Framework for evaluating code generation ability of large language models

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and int...