Article
Chemistry, Multidisciplinary
Irfan Khan Tanoli, Imran Amin, Faraz Junejo, Nukman Yusoff
Summary: With the growing popularity of online social networks, people desire to use social networking services to establish social relations. However, the privacy policies expressed in natural language cannot automatically control the entities that operate on user data. This paper proposes a method to translate privacy statements from natural language into a controlled natural language to improve machine processing. The method combines natural language processing techniques, logic programming, and ontologies. The effectiveness and efficiency of the developed system were tested with data privacy policies from different social network service providers.
APPLIED SCIENCES-BASEL
(2022)
Review
Computer Science, Information Systems
Miguel A. Alvarez-Carmona, Ramon Aranda, Ansel Y. Rodriguez-Gonzalez, Daniel Fajardo-Delgado, Maria Guadalupe Sanchez, Humberto Perez-Espinosa, Juan Martinez-Miranda, Rafael Guerrero-Rodriguez, Lazaro Bustio-Martinez, Angel Diaz-Pacheco
Summary: The social networks and advancements in technology have greatly impacted the tourism industry. Natural language processing (NLP) in artificial intelligence is particularly beneficial for gathering information on user-generated content related to tourism services and products. This study conducts a systematic review of the use of NLP in the tourism industry, analyzing methodologies, tools, data sources, and other relevant features. It also introduces a taxonomy for using NLP in tourism and identifies six major topics in applying NLP to tourism issues. The analysis of metadata reveals similarities in tourism issues or approaches among China, the United States, Thailand, and Spain.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Review
Computer Science, Theory & Methods
Yohan Bonescki Gumiel, Lucas Emanuel Silva e Oliveira, Vincent Claveau, Natalia Grabar, Emerson Cabrera Paraiso, Claudia Moro, Deborah Ribeiro Carvalho
Summary: Temporal relation extraction in clinical texts is a major research focus, with attention-based models being the current state-of-the-art. However, further experiments and research advancements are still needed. Additionally, dataset imbalance and task complexity directly impact system performance, requiring new annotation projects to provide datasets for different medical specialties and languages.
ACM COMPUTING SURVEYS
(2021)
Review
Computer Science, Theory & Methods
Luciano Ignaczak, Guilherme Goldschmidt, Cristiano Andre Da Costa, Rodrigo Da Rosa Righi
Summary: The article discusses the application of text mining in the cybersecurity domain to improve activity efficiency and proposes a taxonomy to demonstrate the different activities supported by text mining. It also discusses text classification performance, neural network support, and highlights future research directions.
ACM COMPUTING SURVEYS
(2021)
Review
Computer Science, Information Systems
Nathaniel Linna, Charles E. Kahn
Summary: In the past five years, there has been an increasing study and more accurate application of NLP in radiology. However, challenges remain in the clinical application and portability of NLP techniques in radiology.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2022)
Review
Chemistry, Multidisciplinary
Ali Saleh Alammary
Summary: BERT has gained attention for its unique features in natural language processing, with the introduction of models supporting different languages like Arabic. However, the current state of applying BERT to Arabic text classification is limited, prompting the need for further research and improvements.
APPLIED SCIENCES-BASEL
(2022)
Review
Computer Science, Information Systems
Samar Bashath, Nadeesha Perera, Shailesh Tripathi, Kalifa Manjang, Matthias Dehmer, Frank Emmert Streib
Summary: In recent years, deep learning models have been widely used in many applications. However, traditional learning paradigms do not always hold for real-world data. In such cases, transfer learning can provide solutions by transferring information from data-rich sources to data-sparse targets. This paper surveys deep transfer learning models in the context of text data and introduces a new nomenclature and visual taxonomy.
INFORMATION SCIENCES
(2022)
Review
Computer Science, Cybernetics
Rosa Lilia Segundo Diaz, Gustavo Rovelo Ruiz, Miriam Bouzouita, Karin Coninx
Summary: Designing serious games that engage lots of players is still a challenge. Researchers have investigated the relationship between enjoyment and game design elements, but these efforts remain dispersed across different areas. This paper provides a systematic literature review to understand the relationship between game design elements, player enjoyment, and evaluation tools. Additionally, successful case analyses highlight the impact of game design elements on player enjoyment.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES
(2022)
Review
Computer Science, Information Systems
Somiya Rani, Amita Jain
Summary: The explosion of clinical textual data has become a concern for researchers due to the difficulty healthcare professionals face in taking real-time measures. This review surveys the use of deep learning methods in the healthcare domain, such as CNN, RNN, LSTM, and GRU, for text processing. Various applications including clinical concept detection and extraction, medically aware dialogue systems, sentiment analysis of drug reviews, clinical trial matching, and pharmacovigilance are discussed. The challenges and future research scope in deploying text processing with deep learning to clinical textual data are highlighted, along with potential resources for optimizing the healthcare domain.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Information Systems
Connor T. Dodd, Marc T. P. Adam, Megan E. Rollo
Summary: This paper reviews the current state of using speech records for dietary assessment. The findings reveal the potential of speech recording in reducing barriers and increasing user acceptance. Unstructured speech recording is preferred among different methods. Automated speech transcription shows high accuracy, and natural language processing further automates analysis with satisfactory accuracy. Further research is needed to address practical challenges in dietary assessment and monitoring.
Review
Computer Science, Information Systems
Irene Li, Jessica Pan, Jeremy Goldwasser, Neha Verma, Wai Pan Wong, Muhammed Yavuz Nuzumlali, Benjamin Rosand, Yixin Li, Matthew Zhang, David Chang, R. Andrew Taylor, Harlan M. Krumholz, Dragomir Radev
Summary: Electronic health records (EHRs) are digital collections of patient healthcare events and observations that play a critical role in healthcare delivery, operations, and research. However, a significant portion of the information stored in EHRs is unstructured text, making it challenging to process automatically. Recent advances in neural network and deep learning methods for Natural Language Processing have shown promise in unlocking the potential of this unstructured text in EHRs.
COMPUTER SCIENCE REVIEW
(2022)
Review
Computer Science, Information Systems
Ivan Otero-Gonzalez, Moises R. Pacheco-Lorenzo, Manuel J. Fernandez-Iglesias, Luis E. Anido-Rifon
Summary: This study explores the applications of conversational agents in detecting mental health disorders, specifically depression screening. The findings indicate that conversational agents are effective in detecting depression, and voice interaction is the future direction of development.
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS
(2024)
Review
Computer Science, Artificial Intelligence
Ahlam Wahdan, Mostafa Al-Emran, Khaled Shaalan
Summary: This article provides an overview of the current status of Arabic text classification, including research methods, topic areas, and application tasks. The study finds that there is a lack of thorough evaluation of Arabic text classification. The article proposes directions for further research, such as addressing the issue of unbalanced datasets and improving the preprocessing phase.
Review
Computer Science, Artificial Intelligence
Dadi Ramesh, Suresh Kumar Sanampudi
Summary: Assessment in the education system is vital in determining student performance, with manual evaluation processes facing challenges like time consumption and reliability. Online examination systems have been developed as an alternative, especially for grading essays and short answers.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Review
Medical Informatics
Arlene Casey, Emma Davidson, Michael Poon, Hang Dong, Daniel Duma, Andreas Grivas, Claire Grover, Victor Suarez-Paniagua, Richard Tobin, William Whiteley, Honghan Wu, Beatrice Alex
Summary: NLP plays a significant role in extracting structured information from radiology reports, but recent reviews on this topic are limited. This study systematically assesses recent literature in NLP applied to radiology reports and finds that research in this field continues to grow. Deep learning is increasingly used, but conventional machine learning approaches are still prevalent.
BMC MEDICAL INFORMATICS AND DECISION MAKING
(2021)
Article
Computer Science, Interdisciplinary Applications
Taxiarchis Botsis, Christopher Jankosky, Deepa Arya, Kory Kreimeyer, Matthew Foster, Abhishek Pandey, Wei Wang, Guangfan Zhang, Richard Forshee, Ravi Goud, David Menschik, Mark Walderhaug, Emily Jane Woo, John Scott
JOURNAL OF BIOMEDICAL INFORMATICS
(2016)
Article
Computer Science, Interdisciplinary Applications
Wei Wang, Kory Kreimeyer, Emily Jane Woo, Robert Ball, Matthew Foster, Abhishek Pandey, John Scott, Taxiarchis Botsis
JOURNAL OF BIOMEDICAL INFORMATICS
(2016)
Article
Medical Informatics
Taxiarchis Botsis, Matthew Foster, Nina Arya, Kory Kreimeyer, Abhishek Pandey, Deepa Arya
APPLIED CLINICAL INFORMATICS
(2017)
Article
Health Care Sciences & Services
Abhishek Pandey, Kory Kreimeyer, Matthew Foster, Oanh Dang, Thomas Ly, Wei Wang, Richard Forshee, Taxiarchis Botsis
HEALTH INFORMATICS JOURNAL
(2019)
Article
Immunology
Matthew Foster, Abhishek Pandey, Kory Kreimeyer, Taxiarchis Botsis
