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View article: Hierarchical Blockmodeling for Knowledge Graphs
Hierarchical Blockmodeling for Knowledge Graphs Open
In this article, we investigate the use of probabilistic graphical models, specifically stochastic blockmodels, for the purpose of hierarchical entity clustering on knowledge graphs. These models, seldom used in the Semantic Web community,…
View article: Construction of Topic Hierarchy with Subtree Representation for Knowledge Graphs
Construction of Topic Hierarchy with Subtree Representation for Knowledge Graphs Open
Hierarchy analysis of the knowledge graphs aims to discover the latent structure inherent in knowledge base data. Drawing inspiration from topic modeling, which identifies latent themes and content patterns in text corpora, our research se…
View article: Can LLMs serve in identifying fake Health Information: it depends on how and who you ask. (Preprint)
Can LLMs serve in identifying fake Health Information: it depends on how and who you ask. (Preprint) Open
UNSTRUCTURED Misleading information has significant implications for society but can have disastrous impact for health matters. Transformative artificial intelligence (AI) tools such as large language models (LLMs) have the potential for …
View article: Hierarchical Blockmodelling for Knowledge Graphs
Hierarchical Blockmodelling for Knowledge Graphs Open
In this paper, we investigate the use of probabilistic graphical models, specifically stochastic blockmodels, for the purpose of hierarchical entity clustering on knowledge graphs. These models, seldom used in the Semantic Web community, d…
View article: Validity and accuracy of automatic cobb angle measurement on 3D spinal ultrasonographs for children with adolescent idiopathic scoliosis: SOSORT 2024 award winner
Validity and accuracy of automatic cobb angle measurement on 3D spinal ultrasonographs for children with adolescent idiopathic scoliosis: SOSORT 2024 award winner Open
Purpose Ultrasonography for scoliosis is a novel imaging method that does not expose children with adolescent idiopathic scoliosis (AIS) to radiation. A single ultrasound scan provides 3D spinal views directly. However, measuring ultrasono…
View article: Using machine learning to automatically measure kyphotic and lordotic angle measurements on radiographs for children with adolescent idiopathic scoliosis
Using machine learning to automatically measure kyphotic and lordotic angle measurements on radiographs for children with adolescent idiopathic scoliosis Open
Measuring the kyphotic angle (KA) and lordotic angle (LA) on lateral radiographs is important to truly diagnose children with adolescent idiopathic scoliosis. However, it is a time-consuming process to measure the KA because the endplate o…
View article: Validity of a fast automated 3d spine reconstruction measurements for biplanar radiographs: SOSORT 2024 award winner
Validity of a fast automated 3d spine reconstruction measurements for biplanar radiographs: SOSORT 2024 award winner Open
Purpose To validate a fast 3D biplanar spinal radiograph reconstruction method with automatic extract curvature parameters using artificial intelligence (AI). Methods Three-hundred eighty paired, posteroanterior and lateral, radiographs fr…
View article: Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial
Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial Open
Families of individuals with neurodevelopmental disabilities or differences (NDDs) often struggle to find reliable health information on the web. NDDs encompass various conditions affecting up to 14% of children in high-income countries, a…
View article: Integrating Quantum CI with Generative AI for Taiwanese/English Co-Learning: TAIDE-based Knowledge Graph Construction and Multimodal Data Transformation
Integrating Quantum CI with Generative AI for Taiwanese/English Co-Learning: TAIDE-based Knowledge Graph Construction and Multimodal Data Transformation Open
This paper proposes a Quantum Computational Intelligence (QCI) model integrated with Generative Artificial Intelligence (GAI) for Taiwanese/English language co-learning applications within human-machine interactions. The QCI model comprise…
View article: Parametric and Nonparametric Machine Learning Techniques for Increasing Power System Reliability: A Review
Parametric and Nonparametric Machine Learning Techniques for Increasing Power System Reliability: A Review Open
Due to aging infrastructure, technical issues, increased demand, and environmental developments, the reliability of power systems is of paramount importance. Utility companies aim to provide uninterrupted and efficient power supply to thei…
View article: Integrating Knowledge Graphs into Distribution Grid Decision Support Systems
Integrating Knowledge Graphs into Distribution Grid Decision Support Systems Open
Distribution grids are complex networks containing multiple pieces of equipment. These components are interconnected, and each of them is described by various attributes. A knowledge graph is an interesting data format that represents piec…
View article: Applying Machine Learning and Point-Set Registration to Automatically Measure the Severity of Spinal Curvature on Radiographs
Applying Machine Learning and Point-Set Registration to Automatically Measure the Severity of Spinal Curvature on Radiographs Open
The developed method measured Cobb angles on radiographs automatically with high accuracy, quick measurement time, and interpretability, suggesting clinical feasibility.
View article: Multi-Level State Evaluation in Complex Systems: Information Granules and Evidence Theory Approach
Multi-Level State Evaluation in Complex Systems: Information Granules and Evidence Theory Approach Open
Real-world systems often exhibit intricate complexity. Navigating and examining the conditions under which these systems operate presents various challenges. These systems are characterized by a web of interconnected inputs and subsystems …
View article: Developing a cluster-based approach for deciphering complexity in individuals with neurodevelopmental differences
Developing a cluster-based approach for deciphering complexity in individuals with neurodevelopmental differences Open
Objective Individuals with neurodevelopmental disorders such as global developmental delay (GDD) present both genotypic and phenotypic heterogeneity. This diversity has hampered developing of targeted interventions given the relative rarit…
View article: Validation of an artificial intelligence-based method to automate Cobb angle measurement on spinal radiographs of children with adolescent idiopathic scoliosis
Validation of an artificial intelligence-based method to automate Cobb angle measurement on spinal radiographs of children with adolescent idiopathic scoliosis Open
Employing the algorithm in practice could streamline clinical workflow and optimize measurement accuracy and speed in order to inform AIS treatment decisions.
View article: Negated Complementary Commonsense using Large Language Models
Negated Complementary Commonsense using Large Language Models Open
Larger language models, such as GPT-3, have shown to be excellent in many tasks. However, we demonstrate that out-of-ordinary questions can throw the model off guard. This work focuses on finding answers to negated complementary questions …
View article: Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial (Preprint)
Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial (Preprint) Open
UNSTRUCTURED Families of individuals with neurodevelopmental disabilities or differences (NDDs) often struggle to find reliable health information on the web. NDDs encompass various conditions affecting up to 14% of children in high-incom…
View article: Reinforcement Learning for Topic Models
Reinforcement Learning for Topic Models Open
We apply reinforcement learning techniques to topic modeling by replacing the variational autoencoder in ProdLDA with a continuous action space reinforcement learning policy. We train the system with a policy gradient algorithm REINFORCE. …
View article: Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study
Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study Open
Background Patients and families need to be provided with trusted information more than ever with the abundance of online information. Several organizations aim to build databases that can be searched based on the needs of target groups. O…
View article: Human intelligence-based metaverse for co-learning of students and smart machines
Human intelligence-based metaverse for co-learning of students and smart machines Open
View article: Probabilistic Coarsening for Knowledge Graph Embeddings
Probabilistic Coarsening for Knowledge Graph Embeddings Open
Knowledge graphs have risen in popularity in recent years, demonstrating their utility in applications across the spectrum of computer science. Finding their embedded representations is thus highly desirable as it makes them easily operate…
View article: Diversifying Top-k Answers in a Query by Example Setting
Diversifying Top-k Answers in a Query by Example Setting Open
View article: Reinforcement Learning for Topic Models
Reinforcement Learning for Topic Models Open
We apply reinforcement learning techniques to topic modeling by replacing the variational autoencoder in ProdLDA with a continuous action space reinforcement learning policy. We train the system with a policy gradient algorithm REINFORCE. …
View article: Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study (Preprint)
Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study (Preprint) Open
BACKGROUND Patients and families need to be provided with trusted information more than ever with the abundance of online information. Several organizations aim to build databases that can be searched based on the needs of target groups. …
View article: Fusion of Multi-level Granular Data using Evidence Theory
Fusion of Multi-level Granular Data using Evidence Theory Open
Complex systems are often composed of multiple subsystems arranged in a multi-level hierarchical structure. Therefore, dedicated methods suitable for determining the local states of such arranged components and the global state of the syst…
View article: Title Page III
Title Page III Open
View article: Utilizing Language Models to Expand Vision-Based Commonsense Knowledge Graphs
Utilizing Language Models to Expand Vision-Based Commonsense Knowledge Graphs Open
The introduction and ever-growing size of the transformer deep-learning architecture have had a tremendous impact not only in the field of natural language processing but also in other fields. The transformer-based language models have con…
View article: Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing
Deciphering the Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing Open
Background Understanding how individuals think about a topic, known as the mental model, can significantly improve communication, especially in the medical domain where emotions and implications are high. Neurodevelopmental disorders (NDDs…
View article: Deciphering Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing (Preprint)
Deciphering Diversity of Mental Models in Neurodevelopmental Disorders: Knowledge Graph Representation of Public Data Using Natural Language Processing (Preprint) Open
BACKGROUND Understanding how individuals think about a topic can help to significantly improve communication. This is especially true when it comes to the medical domain where emotion and implications are high. Neurodevelopmental disorder…
View article: Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce Data Annotation Required in Visual Commonsense Tasks
Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce Data Annotation Required in Visual Commonsense Tasks Open
Pre-trained language models have shown excellent results in few-shot learning scenarios using in-context learning. Although it is impressive, the size of language models can be prohibitive to make them usable in on-device applications, suc…