ORCID Profile
0000-0002-0120-2582
Current Organisation
Swinburne University of Technology
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Publisher: JMIR Publications Inc.
Date: 19-01-2017
Publisher: IEEE
Date: 05-2020
Publisher: arXiv
Date: 2021
Publisher: arXiv
Date: 2021
Publisher: arXiv
Date: 2021
Publisher: Elsevier BV
Date: 07-2021
Publisher: Association for Computational Linguistics
Date: 2021
Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
Date: 19-06-2014
Abstract: For expressive ontology languages such as OWL 2 DL, classification is a computationally expensive task—2NEXPTIME-complete in the worst case. Hence, it is highly desirable to be able to accurately estimate classification time, especially for large and complex ontologies. Recently, machine learning techniques have been successfully applied to predicting the reasoning hardness category for a given (ontology, reasoner) pair. In this paper, we further develop predictive models to estimate actual classification time using regression techniques, with ontology metrics as features. Our large-scale experiments on 6 state-of-the-art OWL 2 DL reasoners and more than 450 significantly erse ontologies demonstrate that the prediction models achieve high accuracy, good generalizability and statistical significance. Such prediction models have a wide range of applications. We demonstrate how they can be used to efficiently and accurately identify performance hotspots in a large and complex ontology, an otherwise very time-consuming and resource-intensive task.
Publisher: Elsevier BV
Date: 2023
Publisher: Springer International Publishing
Date: 2015
Publisher: IEEE
Date: 06-2020
Publisher: Elsevier BV
Date: 2020
Publisher: JMIR Publications Inc.
Date: 22-09-2022
DOI: 10.2196/39013
Abstract: Resilience is an accepted strengths-based concept that responds to change, adversity, and crises. This concept underpins both personal and community-based preventive approaches to mental health issues and shapes digital interventions. Online mental health peer-support forums have played a prominent role in enhancing resilience by providing accessible places for sharing lived experiences of mental issues and finding support. However, little research has been conducted on whether and how resilience is realized, hindering service providers’ ability to optimize resilience outcomes. This study aimed to create a resilience dictionary that reflects the characteristics and realization of resilience within online mental health peer-support forums. The findings can be used to guide further analysis and improve resilience outcomes in mental health forums through targeted moderation and management. A semiautomatic approach to creating a resilience dictionary was proposed using topic modeling and qualitative content analysis. We present a systematic 4-phase analysis pipeline that preprocesses raw forum posts, discovers core themes, conceptualizes resilience indicators, and generates a resilience dictionary. Our approach was applied to a mental health forum run by SANE (Schizophrenia: A National Emergency) Australia, with 70,179 forum posts between 2018 and 2020 by 2357 users being analyzed. The resilience dictionary and taxonomy developed in this study, reveal how resilience indicators (ie, “social capital,” “belonging,” “learning,” “adaptive capacity,” and “self-efficacy”) are characterized by themes commonly discussed in the forums each theme’s top 10 most relevant descriptive terms and their synonyms and the relatedness of resilience, reflecting a taxonomy of indicators that are more comprehensive (or compound) and more likely to facilitate the realization of others. The study showed that the resilience indicators “learning,” “belonging,” and “social capital” were more commonly realized, and “belonging” and “learning” served as foundations for “social capital” and “adaptive capacity” across the 2-year study period. This study presents a resilience dictionary that improves our understanding of how aspects of resilience are realized in web-based mental health forums. The dictionary provides novel guidance on how to improve training to support and enhance automated systems for moderating mental health forum discussions.
Publisher: Wiley
Date: 25-12-2019
DOI: 10.1002/WIDM.1350
Abstract: Healthcare 4.0 is a term that has emerged recently and derived from Industry 4.0. Today, the health care sector is more digital than in past decades for ex le, spreading from x‐rays and magnetic resonance imaging to computed tomography and ultrasound scans to electric medical records. With the wide spectrum of digital technologies underpinning Healthcare 4.0 to deliver more effective and efficient health care services, in this article, we use the wisdom pyramid methodology to conduct a systematic review of current digital frontiers in Healthcare 4.0. This article is categorized under: Technologies Computer Architectures for Data Mining Application Areas Health Care Application Areas Data Mining Software Tools Fundamental Concepts of Data and Knowledge Knowledge Representation
Publisher: IEEE
Date: 06-2009
Publisher: Elsevier BV
Date: 02-2022
Publisher: Springer Science and Business Media LLC
Date: 03-09-2021
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2016
Publisher: Elsevier BV
Date: 05-2022
Publisher: SAGE Publications
Date: 21-10-2023
DOI: 10.1177/00938548221131952
Abstract: Pre-sentence reports (PSRs) provide important information about an in idual’s background and circumstances to assist judicial officers in the sentencing process. The present study analyzed PSRs for 63 Aboriginal and Torres Strait Islander people sentenced by either an Indigenous sentencing court or a mainstream court in the Australian State of Victoria. Using natural language processing techniques, our analyses revealed few differences between PSRs conducted for each court. However, PSRs were found to predominantly feature key words that are risk-based, with mainstream court PSRs more negatively worded than the Indigenous sentencing court’s PSRs. This may have been due to the inclusion of results from a risk and need assessment tool. Pro-social factors did comprise more than one third of extracted keywords, although the number of strength-based culture-related keywords, in particular, was low across PSRs in both courts. It is possible that courts may not be receiving all the information needed to promote in idualized justice.
Publisher: arXiv
Date: 2021
Publisher: Hawaii International Conference on System Sciences
Date: 2022
Publisher: JMIR Publications Inc.
Date: 25-04-2022
Abstract: esilience is an accepted strengths-based concept responding to change, adversity and crisis that involves a range of environmental, social and personal adaptive factors. The concept underpins both personal and community-based preventative approaches to mental health issues and has shaped digital interventions. Online peer-support mental health forums have played a prominent role in enhancing resilience by providing accessible places for sharing lived experiences of mental issues and finding support. Despite the significance and viability of such forums for complementing mental health care, there has been little research on whether and how resilience is realised, hindering service providers’ ability to demonstrate impact. his paper aims to create a resilience dictionary that reflects the characteristics and realisation of resilience within online mental health peer-support forums. The findings can be used to guide further analysis and inform strengths-based moderation and management of mental health forums. semi-automatic approach to creating a resilience dictionary is proposed using topic modelling and qualitative content analysis. We present a systematic four-phase analysis pipeline that pre-processes raw forum posts, discovers main themes being discussed in the posts, conceptualises resilience indicators, and resilience dictionary creation. Our approach is applied to online peer-support mental health forums from 2018 to 2020 in SANE Australia, where 70,179 forum post data used by 2,357 users were collected and explored in this study. he resilience dictionary and taxonomy developed in this study, reveal: (1) how resilience indicators (i.e., “social capital”, “belonging”, “learning”, “adaptive capacity”, and “self-efficacy”) are characterised by themes commonly discussed on the forums (2) each theme’s top-10 most relevant descriptive terms and their synonyms and (3) the relatedness of resilience, reflecting a taxonomy of indicators that are more comprehensive (or compound) and indicators that are more likely to facilitate the realisation of others. The study also presents the four-phase analysis pipeline that constructs a resilience dictionary from new forum datasets. Further, this study identifies the resilience indicators “learning”, “belonging” and “social capital” are more commonly realised resilience indicators, and "learning" and "belonging" serve as foundations for the realisation of “self-efficacy” and “adaptive capacity” across the two-year study period. his paper presents a resilience dictionary that improves our understanding of how aspects of resilience are realised in online mental health forums. The dictionary provides novel guidance on how to improve training to support and enhance automated systems for moderating mental health forum discussions.
Publisher: Elsevier BV
Date: 05-2023
Publisher: Elsevier BV
Date: 05-2021
Publisher: ACM
Date: 07-10-2015
Publisher: ACM
Date: 22-03-2010
Publisher: ACM
Date: 03-11-2014
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Elsevier BV
Date: 07-2014
No related grants have been discovered for Yong-Bin Kang.