Article
Computer Science, Information Systems
Pu Li, Guohao Zhou, Yanbu Guo, Suzhi Zhang, Yuncheng Jiang, Yong Tang
Summary: Since the outbreak of COVID-19, this paper proposes a new three-stage annotation method and constructs an epidemiological investigation dataset for Chinese named entity recognition (CNER) to effectively analyze and utilize the reports. The SECCSF method improves the accuracy of segmentation and entity category determination. The experiments show the effectiveness of the SECCSF method on the EPIC dataset.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Zhou Yang, Yucai Pang, Xuehong Li, Qian Li, Shihong Wei, Rong Wang, Yunpeng Xiao
Summary: This study proposes a rumor detection model based on topic audiolization, which transforms the topic space into audio-like signals. Experimental results show that the model achieves significant performance improvements in rumor identification.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Information Science & Library Science
Youngok Choi, Emma Brodfuehrer Hastings
Summary: Exhibits are increasingly used by academic libraries as a means of outreach. This study examined digital exhibits created by ARL-member academic library systems to explore their nature and use. The findings confirm that academic librarians use digital exhibits to highlight collections, inform and entertain visitors, contribute to student instruction, and strengthen relationships with various communities through collaborative exhibit creation.
JOURNAL OF ACADEMIC LIBRARIANSHIP
(2024)
Article
Computer Science, Information Systems
Xueyang Qin, Lishang Li, Fei Hao, Meiling Ge, Guangyao Pang
Summary: Image-text retrieval is important in connecting vision and language. This paper proposes a method that utilizes prior knowledge to enhance feature representations and optimize network training for better retrieval results.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Review
Computer Science, Information Systems
Gang Ren, Lei Diao, Fanjia Guo, Taeho Hong
Summary: This paper proposes a novel approach for predicting the helpfulness of reviews by utilizing both textual and image features. The proposed method considers the correlation between features through self-attention and co-attention mechanisms, and fuses multi-modal features for prediction. Experimental results demonstrate the superior performance of the proposed method compared to benchmark methods.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Ying Zhao, Tingyu Xia, Yunqi Jiang, Yuan Tian
Summary: This paper presents an Enhanced Inter-sentence Attention (EIA) architecture to improve the task of semantic textual similarity (STS). The architecture integrates enhanced inter-sentence attention with original attention through a gated fusion module, effectively incorporating important inter-sentence information. Experiments show that EIA achieves improved performance on benchmark datasets.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Jiahao Yang, Shuo Feng, Wenkai Zhang, Ming Zhang, Jun Zhou, Pengyuan Zhang
Summary: To pursue profit from stock markets, researchers utilize deep learning methods to forecast asset price movements. However, there are two issues in current research, the discrepancy between forecasting results and profits, and heavy reliance on prior knowledge. To address these issues, researchers propose a novel optimization objective and modeling method, and conduct experiments to validate their approach.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Ying Hu, Yanping Chen, Ruizhang Huang, Yongbin Qin, Qinghua Zheng
Summary: Biomedical relation extraction aims to extract the interactive relations between biomedical entities in a sentence. This study proposes a hierarchical convolutional model to address the semantic overlapping and data imbalance problems. The model encodes both local contextual features and global semantic dependencies, enhancing the discriminability of the neural network for biomedical relation extraction.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xuan Zhang, Wei Gao
Summary: In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors and identifying vulnerable users. A novel approach using a unified graph neural network model is proposed to predict viral rumors and vulnerable users. The evaluation results confirm the superiority of the approach in rumor detection, virality prediction, and user vulnerability scoring.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Information Science & Library Science
Michal Biron, Keren Turgeman-Lupo, Orna Zaid-Dominik
Summary: This research explores the relationship between retiring employees' knowledge continuity behavior and the usefulness of imparted knowledge to recipients' post-departure performance, and finds that transformational leadership and innovation culture have an impact on this relationship.
KNOWLEDGE MANAGEMENT RESEARCH & PRACTICE
(2023)
Article
Information Science & Library Science
Yafei Feng, Yan Zhang, Lifu Li
Summary: This study explores the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective based on collective privacy calculus theory and impression management theory. The findings show that self-presentation and others presentation directly positively affect users' co-owned information disclosure. Additionally, self-presentation, others presentation, and relationship presentation indirectly positively affect users' co-owned information disclosure via relationship support, while personal privacy concern, others' privacy concern, and relationship privacy concern indirectly negatively affect users' co-owned information disclosure via relationship risk.
Article
Information Science & Library Science
Wantao Yu, Qi Liu, Roberto Chavez, Linchang Zheng
Summary: This study examines the impact of digital transformation on environmental sustainability, and investigates the moderating role of training provision. The findings suggest that digital transformation has a positive impact on environmental sustainability, and this effect is strengthened by training provision.
INFORMATION TECHNOLOGY & PEOPLE
(2023)
Article
Information Science & Library Science
Lijing Zhao, Maria Khalid, Abdul Karim Khan, Yufei Ma
Summary: Drawing on social exchange theory, this study examined the impact of negative workplace gossip on knowledge hiding behaviors. The results showed that negative workplace gossip has a positive association with knowledge hiding behaviors, which is mediated by duty orientation. Additionally, psychological entitlement strengthens the negative influence of negative workplace gossip on duty orientation. However, the indirect effect of negative workplace gossip on knowledge hiding behaviors through duty orientation is stronger for employees with high psychological entitlement compared to those with low levels of psychological entitlement.
KNOWLEDGE MANAGEMENT RESEARCH & PRACTICE
(2023)
Article
Computer Science, Interdisciplinary Applications
Hui Li, Xingmei Zhang
Summary: Authorship is the core of academic research reward system, but the study shows the existence of over 1.4 million anonymous publications in the past century, which poses a threat to authorship-based research evaluation and scholarly communication systems. Although the number of anonymous citable items has been decreasing, it still remains significant in fields like Law. Journals like Harvard Law Review continue the tradition of anonymous publishing, which deserves more attention regarding its impact on research evaluation and scholarly communication.
Article
Information Science & Library Science
Susan Gardner Archambault
Summary: This study explores subject-matter experts' insights and perceptions of the knowledge components, coping behaviors, and pedagogical considerations in teaching algorithmic literacy to postsecondary students, and contributes to improved pedagogy and validation of existing conceptualizations and measurements of algorithmic literacy.
INFORMATION AND LEARNING SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Alberto Baccini, Federica Baccini, Lucio Barabesi, Martina Cioni, Eugenio Petrovich, Daria Pignalosa
Summary: By utilizing multiple sources of information and applying similarity network fusion, a fine-grained classification of journal articles is achieved. The results show that similarity network fusion is the best option in some cases and the classification obtained accurately represents the heterogeneity of the journal articles.
Article
Information Science & Library Science
Riccardo Punis, Alfonso Zoleo
Summary: Copper complexes (or soaps) have significant implications for the conservation of historical artefacts, and electron paramagnetic resonance spectroscopy can serve as a tool for their identification. Through experimentation using mock-up systems, we have demonstrated that this technique can accurately characterize copper complexes.
RESTAURATOR-INTERNATIONAL JOURNAL FOR THE PRESERVATION OF LIBRARY AND ARCHIVAL MATERIAL
(2023)
Article
Computer Science, Information Systems
Laurie Hughes, Jonathan J. M. Seddon, Yogesh K. Dwivedi
Summary: The digital transformation of the FinTech industry brings various challenges, including new regulatory frameworks, legacy systems, flexible business models, and corporate social responsibility practice. This study adopts a mixed methods approach to uncover the interdependencies and priorities of challenges, such as investment in new market products and infrastructure, stakeholder support, and the development of a digital mindset.
JOURNAL OF INFORMATION TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Suha Alawadhi, Husain Alansari, Ahmad R. Alsaber
Summary: This study investigates the factors influencing users' trust in and use of e-government services. The results show that information quality and design, as well as perceived ease of use, affect users' trust and behavioral intentions. Gender and nationality also have a significant impact on users' satisfaction with e-government services.
SOCIAL SCIENCE COMPUTER REVIEW
(2023)
Article
Computer Science, Information Systems
Anjun Chen, Drake O. Chen, Lu Tian
Summary: This study evaluates the symptom-checking accuracy of ChatGPT for a broad range of diseases using the Mayo Clinic Symptom Checker patient service as a benchmark. The results show that ChatGPT exhibits high accuracy, surpassing the previous GPT-3.5-turbo model, and demonstrating its potential as a medical training tool in learning health systems to enhance care quality and address health disparities.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
