Article
Health Care Sciences & Services
Iris Hendrickx, Tim Voets, Pieter van Dyk, Rudolf B. Kool
Summary: This study explored the use of text mining techniques to analyze patient complaint databases in order to identify potential patient safety problems at health care providers and automatically predict the severity of complaints. The research found that a simple text classification approach using bag-of-words feature representation worked best for severity prediction of complaints, achieving high accuracy rates on the test set.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
JeeHee Lee, Youngjib Ham, June-Seong Yi
Summary: This study used text mining methods to examine a large amount of construction legal cases, exploring the types of contract conditions frequently referenced in the final decisions of disputes. The findings indicate that similar patterns of disputes occur repeatedly in construction-related legal cases, and the discovered dispute topics suggest that mutually agreed upon contract terms and conditions are important in dispute resolution.
Article
Biochemical Research Methods
Kaiyin Zhou, Yuxing Wang, Kevin Bretonnel Cohen, Jin-Dong Kim, Xiaohang Ma, Zhixue Shen, Xiangyu Meng, Jingbo Xia
Summary: The study bridges heterogeneous mutation data to predict disease-related genes using the GDAMDB pipeline, successfully identifying multiple genes associated with Alzheimer's disease. Some genes are supported by other studies or literature reports, while others are newly predicted.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Chemistry, Multidisciplinary
Minsu Cho, Gyunam Park, Minseok Song, Jinyoun Lee, Euiseok Kum
Summary: This paper focuses on developing a new method for deriving a quality-aware resource model by integrating resource-oriented transition system and quality-based superior and inferior cases. The proposed method also includes a model simplification technique based on statistical analyses for better visualization. Tooling support and a case study in semiconductor manufacturing process are presented to demonstrate the practical applicability of the approach.
APPLIED SCIENCES-BASEL
(2021)
Review
Computer Science, Artificial Intelligence
Gyunam Park, Minsu Cho, Jiyoon Lee
Summary: This article provides an in-depth analysis of process mining using text mining and machine learning techniques, including main research fields, relationships between fields, and future development trends.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Energy & Fuels
Huifang Wang, Jing Cao, Dongyang Lin
Summary: This paper introduces a text mining method based on semantic framework technology to transform unstructured defect description into structured information. A deep analyzing model of a power equipment defect is established, providing a scheme of defect mining based on historical defect texts. The proposed method has a guiding significance for equipment upgrading, selection, and maintenance, as proven by case studies.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Engineering, Industrial
Hendrik Jacobsen, Kim Hua Tan
Summary: Increased digitalization improves food safety demands, with food producers utilizing sensor monitoring systems for quality management. Existing studies focus on standalone model development, while this paper proposes a scalable association rule model.
PRODUCTION PLANNING & CONTROL
(2022)
Review
Biochemical Research Methods
Liang Chen, Changliang Wang, Huiyan Sun, Juexin Wang, Yanchun Liang, Yan Wang, Garry Wong
Summary: Circular RNAs (circRNAs) are a unique class of RNA molecules produced by back-splicing of linear RNA, and recent advances in sequencing technologies and bioinformatics tools have greatly expanded our understanding of their biological functions and practical applications. There are now numerous bioinformatics tools available for circRNA annotation, identification, and network analysis, which continue to evolve to support various research projects in this field.
BRIEFINGS IN BIOINFORMATICS
(2021)
Review
Management
Mohammad Reza Sadeghi Moghadam, Hossein Safari, Narjes Yousefi
Summary: This paper reviews the history and trends of quality management, classifies quality management techniques, maps out the relevant tools and techniques, and explains the implementation effects studied by scholars.
TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE
(2021)
Article
Computer Science, Artificial Intelligence
Dongliang Zhang, Mingchao Li, Dan Tian, Lingguang Song, Yang Shen
Summary: This research applies text mining to extract hidden information from unstructured quality records and improve the integration and classification of quality records through an enhanced CNN model and quantification using BERT and Word2vec methods. The proposed model achieves high precision with less manual intervention required.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Business
Xinwei Li, Mao Xu, Wenjuan Zeng, Ying Kei Tse, Hing Kai Chan
Summary: The COVID-19 pandemic has had an impact on customers' grocery shopping behaviors. This study uses text-mining techniques and time series analysis to analyze tweets from UK supermarkets during the first lockdown. The results show the causes of sentiment change and how customers perceive supermarkets' response actions. It suggests that engaging in social media crisis communication with customers can benefit grocery companies.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2023)
Article
Business
MyoungHoon Lee, Suhyeon Kim, Hangyeol Kim, Junghye Lee
Summary: To capture emerging technologies in the fast-changing technology market, this study proposes a new technology opportunity discovery framework that uses text mining and a knowledge graph to exploit the information from technology, new technology-based firms (NTBFs), and investors. Empirical results demonstrate the accuracy and validity of the framework.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Engineering, Industrial
Hossein Toosi, Mohammad Amin Ghaaderi, Zahra Shokrani
Summary: This study aims to compare academic project management research trends in Iran and the World over five-year periods using text mining and the TF-IDF method. The innovative aspect lies in the first-time use of text mining to analyze academic research in project and construction management, as well as the comparison of academic research in the construction industry in Iran with global research.
ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT
(2022)
Article
Pharmacology & Pharmacy
Jiang-Shan Tan, Song Hu, Ting-Ting Guo, Lu Hua, Xiao-Jian Wang
Summary: By text mining and functional enrichment analysis, we identified potential drugs that may have therapeutic effects on connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH).
FRONTIERS IN PHARMACOLOGY
(2022)
Article
Computer Science, Information Systems
Muhammad Qasim Memon, Yu Lu, Penghe Chen, Aasma Memon, Muhammad Salman Pathan, Zulfiqar Ali Zardari
Summary: This study introduces a novel ensemble clustering approach that combines text segmentation and text clustering to address the clustering issues of multi-topic text collections. Experimental results using LDA-ont demonstrate significant improvements and excellent clustering performance.
JOURNAL OF INFORMATION SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Michael A. King, Alan S. Abrahams, Cliff T. Ragsdale
EXPERT SYSTEMS WITH APPLICATIONS
(2015)
Article
Computer Science, Information Systems
Sumali J. Conlon, Alan S. Abrahams, Lakisha L. Simmons
JOURNAL OF COMPUTER INFORMATION SYSTEMS
(2015)
Review
Computer Science, Artificial Intelligence
Matt Winkler, Alan S. Abrahams, Richard Gruss, Johnathan P. Ehsani
DECISION SUPPORT SYSTEMS
(2016)
Article
Computer Science, Information Systems
Kristin Kirk, Alan Abrahams, Peter Ractham
JOURNAL OF COMPUTER INFORMATION SYSTEMS
(2016)
Article
Engineering, Manufacturing
Alan S. Abrahams, Weiguo Fan, G. Alan Wang, Zhongju (John) Zhang, Jian Jiao
PRODUCTION AND OPERATIONS MANAGEMENT
(2015)
Article
Public, Environmental & Occupational Health
David M. Goldberg, Samee Khan, Nohel Zaman, Richard J. Gruss, Alan S. Abrahams
Summary: Food contamination and food poisoning pose significant risks to consumers, and it is crucial to monitor food safety rapidly. This study utilizes text mining and machine learning methods to analyze consumer posts in online media and identify interactions with hazardous food products. The results show that this method is more accurate than traditional sentiment analysis and allows for product-level risk assessments. This research provides practical and inexpensive means for real-time monitoring of food safety.
Article
Business, Finance
Lukui Huang, Alan Abrahams, Peter Ractham
Summary: Financial statement fraud is a global problem, and in fraud detection, the cost of false negative is higher than false positive. This study proposes a cost-sensitive cascade forest model for fraud detection and explores the impact of different missing data treatments on prediction performance.
INTELLIGENT SYSTEMS IN ACCOUNTING FINANCE & MANAGEMENT
(2022)
Article
Health Care Sciences & Services
Namrata Mali, Felipe Restrepo, Alan Abrahams, Laura Sands, David M. Goldberg, Richard Gruss, Nohel Zaman, Wendy Shields, Elise Omaki, Johnathon Ehsani, Peter Ractham, Laddawan Kaewkitipong
Summary: This study analyzed online reviews to investigate injury types and contexts resulting from the use of mobility-assistive devices by older adults. The results revealed that many injuries associated with these devices could be preventable through educating patients and caregivers on evaluating the potential future injury risks of the equipment.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Review
Computer Science, Artificial Intelligence
David M. Goldberg, Alan S. Abrahams
Summary: Many firms struggle with monitoring product safety due to the potential negative impacts on consumers and financial standings. Monitoring online reviews can provide important safety insights, but the large volume of data poses practical challenges. This study proposes two new methods for identifying safety hazards, which show improvement over traditional approaches and demonstrate promise for cross-category analysis.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Business
Richard Gruss, David Goldberg, Nohel Zaman, Alan Abrahams
Summary: To address the concerns about product safety in online purchasing, the authors developed a software tool that warns shoppers about potential hazards. Through experiments, the authors found that designs incorporating highlighting and scoring can increase safety knowledge, while simpler designs can enhance safety awareness.
Article
Information Science & Library Science
Sultan M. Al-Daihani, Alan Abrahams
JOURNAL OF ACADEMIC LIBRARIANSHIP
(2018)
Article
Business
Kristin Kirk, Peter Ractham, Alan Abrahams
INTERNATIONAL JOURNAL OF NONPROFIT AND VOLUNTARY SECTOR MARKETING
(2016)
Article
Information Science & Library Science
Sultan M. Al-Daihani, Alan Abrahams
JOURNAL OF ACADEMIC LIBRARIANSHIP
(2016)
Article
Information Science & Library Science
Alan S. Abrahams, Reza Barkhi, Eloise Coupey, Cliff T. Ragsdale, Linda G. Wallace
INFORMATION TECHNOLOGY & MANAGEMENT
(2014)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)