Article
Green & Sustainable Science & Technology
Xianyu Zhang, LuCheng Chen, GuoJun Sheng, XiaoPing Lu, Xinguo Ming
Summary: This paper studies the innovation service system for Customer-product Interaction Life Cycle (CILC) in Smart Product Service System (SPSS) under the new model of mass personalization. Firstly, a comprehension service system for CILC in SPSS is proposed to provide the framework and decision-making for enterprises. Secondly, a personalized service recommendation for CILC in SPSS based on improved collaborative filtering algorithm is proposed to expand and enhance the service resources for enterprises. Thirdly, a calculation example of personalized service recommendation for CILC in SPSS is given. The research of this paper extends and complements the theory of SPSS, and provides a reference for enterprises to plan, set, select, carry out, and maintain service items for CILC in SPSS.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Kaihong Zhou, Gang Du, Roger J. Jiao
Summary: With the growing demand for personalization and market competition, service enterprises need to offer personalized service products in a cost-effective manner. This study proposes a hierarchical joint optimization model for designing personalized service product families. A case study of personalized tourism product family design and tourism operations planning demonstrates the feasibility and potential of the proposed method.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Gangyan Xu, Ruibing Zhang, Su Xiu Xu, Xiaofei Kou, Xuan Qiu
Summary: The research proposes a personalized multimodal travel service design based on the Smart Product Service System to address issues with multimodal intercity transport and promote its popularity.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Economics
Jungwon Yeo
Summary: By representing households' entire shopping baskets as a vector of expenditure shares on various grocery products and calculating pairwise cosine similarities, I aim to understand the similarities and differences across consumers in their shopping baskets, as well as the extent to which these similarities can be explained by observable characteristics. I find that households' shopping baskets vary greatly, with demographic profiles and shopping locations only explaining about 13%-16% of their similarities. However, the similarity in shopping locations has the largest explanatory power, highlighting the importance of similarities in the products offered to households in explaining their purchasing patterns.
Article
Business
Li-Ching Ma
Summary: The purpose of market basket analysis is to persuade customers to spend more money by recommending a group of items they are likely to buy. This paper proposes a novel approach for next-group recommendation based on sequential market basket information. Compared to previous methods, this approach provides more opportunities for customers to increase their spending.
ELECTRONIC COMMERCE RESEARCH
(2023)
Article
Economics
Damjan Vavpotic, Karmen Knavs, Ljubica Knezevic Cvelbar
Summary: Understanding tourist visitation patterns is crucial for decision makers to create a smart tourism industry. This article presents a new approach based on market basket analysis using geo-location data shared by tourists on tourism platforms. The approach was tested in Vienna, showing potential for use at the destination level.
Article
Computer Science, Artificial Intelligence
Miao Li, Xuguang Bao, Liang Chang, Tianlong Gu
Summary: This study introduces a deep learning-based model called DBFM, which improves basket recommendation performance by making personalized representations for baskets and integrating low-order and high-order feature patterns. Experiments on three real-world datasets show that the model outperforms existing methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Ali Pourranjbar, Sajjad Shokouhyar
Summary: Due to concerns about e-waste, manufacturers are pressured to adopt sustainable product development. A product-service system (PSS) offers a potential solution. However, research on waste management in product-oriented PSS is lacking. This study evaluates the success of product-oriented PSSs in waste management using social media data and expert opinions.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Construction & Building Technology
Francesco Manca, Nicolo Daina, Aruna Sivakumar, Jayne Wee Xin Yi, Konstantinos Zavistas, Giuliana Gemini, Irene Vegetti, Liam Dargan, Francesco Marchet
Summary: Information and communication technologies, along with behavior-based approaches, are crucial in promoting sustainable cities and addressing urban issues. In the context of the Sharing Cities program, the deployment of a Digital Social Market tool has successfully encouraged active travel in Milan. The study shows that broader engagement with the app is positively correlated with the level of active travel, highlighting the importance of considering lifestyles, attitudes, and social influence in replicating similar initiatives on a larger scale.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Green & Sustainable Science & Technology
Mohammad Hossein Matinju, Hosein Alizadeh, Adam Loch, Vahid Aghaie
Summary: This paper proposes a novel agent-based model (ABM) to assess actual informal water market (IWM) trade. The model development is based on survey and interview data collected from a sample of farmers, and critical human behaviors are described using parameters and formulas. The simulation results reveal that IWM trade improves water resource utilization and contributes to a more stable cultivation area in dry years.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Information Systems
Mauricio A. Valle, Gonzalo A. Ruz
Summary: The level of order or disorder in complex systems is determined by the correlation between system properties. In crises, financial systems tend to synchronize while retail markets exhibit diverse correlation patterns in purchasing behavior. Community detection techniques have been developed to identify similar behavior clusters, but the inherent interactions between system elements are not fully considered.
Article
Business
Seth Ampadu, Yuanchun Jiang, Emmanuel Debrah, Collins Opoku Antwi, Eric Amankwa, Samuel Adu Gyamfi, Richard Amoako
Summary: This study investigates the impact of personalized product quality on e-impulse buying behavior, with results showing a significant positive influence. The relationship between product quality and impulse buying is partially mediated by consumers' affective image and satisfaction. Online reviews also play a moderating role in the direct and indirect relations between product quality and impulse buying.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2022)
Article
Pharmacology & Pharmacy
Chi-Jung Tai, Mohamed El-Shazly, Yi-Hong Tsai, Dezso Csupor, Judit Hohmann, Yang-Chang Wu, Tzyy-Guey Tseng, Fang-Rong Chang, Hui-Chun Wang
Summary: This study utilized artificial intelligence and data mining methods to evaluate the clinical indications of Fuzi in modern practices. The results showed that Fuzi is commonly used in pulmonary, gastrointestinal, and rheumatologic diseases, with patients often having comorbidities such as osteoarthritis, peptic ulcers, hypertension, and COPD. Market basket analysis revealed practical Fuzi-related herbal pairs that could be beneficial for the development of new botanical drugs.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Statistics & Probability
Yuksel Akay Unvan
Summary: This study conducted a Market Basket Analysis using Association Rules on supermarket sales data, revealing that customers who buy Milk, Sweet Relish, and Pepperoni Pizza also purchase eggs, with 24 customers in the dataset fitting this rule.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Management
Emanuele Tresoldi, Federico Malucelli, Maddalena Nonato
Summary: This study focuses on the design of Walking Bus service lines, using arc-based and path-based models, and testing on real instances such as a primary school in Italy.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
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)