A5102803694- Semantic Web and Ontologies
- Logic, Reasoning, and Knowledge
- Topic Modeling
- Natural Language Processing Techniques
- Service-Oriented Architecture and Web Services
- Data Quality and Management
- Rough Sets and Fuzzy Logic
- Advanced Algebra and Logic
- Biomedical Text Mining and Ontologies
- AI-based Problem Solving and Planning
- Advanced Graph Neural Networks
- Structural Health Monitoring Techniques
- Bayesian Modeling and Causal Inference
- Multi-Agent Systems and Negotiation
- Neural Networks and Applications
- Web Data Mining and Analysis
- Multimodal Machine Learning Applications
- Advanced Text Analysis Techniques
- Advanced Database Systems and Queries
- Domain Adaptation and Few-Shot Learning
- Data Mining Algorithms and Applications
- Advanced Image and Video Retrieval Techniques
- Data Management and Algorithms
- Sentiment Analysis and Opinion Mining
- Text and Document Classification Technologies
Southeast University
2014-2024
Batangas State University
2024
Shanghai University
2021
Henan University
2021
TD Bank
2021
Wuhan University
2021
Queen's University Belfast
2004-2012
Jilin University
2012
Karlsruhe Institute of Technology
2007-2011
Southeast University
2006-2010
The cyclic behavior of stratified silty sandy soils is at present poorly understood, yet these materials are commonly found in alluvial deposits and hydraulic fill, which have a history liquefaction during earthquakes. main objective this research project was to compare the homogeneous sands seismic conditions for various silt contents confining pressures. A comprehensive experimental program undertaken total 150 stress-controlled undrained triaxial tests were performed. Two methods sample...
Medication recommendation targets to provide a proper set of medicines according patients' diagnoses, which is critical task in clinics. Currently, the manually conducted by doctors. However, for complicated cases, like patients with multiple diseases at same time, it's difficult propose considerate even experienced This urges emergence automatic medication can help treat diagnosed without causing harmful drug-drug interactions.Due clinical value, has attracted growing research...
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living standards, facilitating rapid expansion areas while efficiently managing resources through sustainable and scalable innovations. In this regard, emerging technologies like Artificial Intelligence (AI), Internet Things (IoT), big data analytics, fog edge computing have become increasingly prevalent, smart city applications grapple with various challenges, including potential for unauthorized disclosure...
Significant progress has been achieved in the active control of civil-engineering structures, not only algorithm, but also testing scale model and full-scale building. At present time, most algorithms used structures are based on optimization instantaneous objective function. In this paper, a Backpropagation-Through-Time Neural Controller (BTTNC) developed for under dynamic loadings is presented. The BTTNC consists two components: (1) Emulator Network to represent structure be controlled;...
ABSTRACT Making medication prescriptions in response to the patient's diagnosis is a challenging task. The number of pharmaceutical companies, their inventory medicines, and recommended dosage confront doctor with well-known problem information cognitive overload. To assist medical practitioner making informed decisions regarding prescription patient, researchers have exploited electronic health records (EHRs) automatically recommending medication. In recent years, recommendation using EHRs...
Measuring inconsistency in knowledge bases has been recognized as an important problem several research areas. Many methods have proposed to solve this and a main class of them is based on some kind paraconsistent semantics. However, existing suffer from two limitations: (i) they are mostly restricted propositional bases; (ii) very few discuss computational aspects computing measures. In article, we try these limitations by exploring algorithms for measure first-order bases. After...
Abstract The early concept of knowledge graph originates from the idea Semantic Web, which aims at using structured graphs to model world and record relationships that exist between things. Currently publishing bases as open data on Web has gained significant attention. In China, CIPS(Chinese Information Processing Society) launched OpenKG in 2015 foster development Chinese Open Knowledge Graphs. Unlike existing knowledge-based programs, chain is envisioned a blockchain-based infrastructure....
The identification and modeling of linear nonlinear dynamic systems through the use measured experimental data is a problem considerable importance in engineering. Among methods, artificial neural network newly developed technique. Due to its attributes, such as parallelism, adaptability, robustness, inherent ability handle nonlinearity, networks have shown great promise function mapping, pattern recognition, image processing, so on. However, including structural model identification, still...
Measuring Inconsistency in ontologies is an important topic ontology engineering as it can provide extra information for dealing with inconsistency. Many approaches have been proposed to deal this issue. However, the main drawback of these algorithms their high computational complexity. One sources complexity intractability underlying Description Logics (DLs). In paper, we focus on tractable DL family, \emph{DL-Lite}. We define inconsistency degree a \emph{DL-Lite} based three-valued...
ABox abduction is an important reasoning facility in Description Logics (DLs). It finds all minimal sets of axioms, called abductive solutions, which should be added to a background ontology enforce entailment observation specified set axioms. However, far from practical by now because there lack feasible methods working finite time for expressive DLs. To pave way abduction, this paper proposes new problem and method computing solutions accordingly. The proposed guarantees number solutions....
The MapReduce framework has proved to be very efficient for data-intensive tasks. Earlier work successfully applied large scale RDFS/OWL reasoning. In this paper, we move a step forward by considering scalable reasoning on semantic data under fuzzy pD* semantics (i.e., an extension of OWL with vagueness). To the best our knowledge, is first investigate how can solve scalability issue in OWL. While most optimizations considered existing are also applicable semantics, unique challenges arise...
Despite their competitive performance on knowledge-intensive tasks, large language models (LLMs) still have limitations in memorizing all world knowledge especially long tail knowledge. In this paper, we study the KG-augmented model approach for solving graph question answering (KGQA) task that requires rich Existing work has shown retrieving KG to enhance LLMs prompting can significantly improve KGQA. However, approaches lack a well-formed verbalization of knowledge, i.e., they ignore gap...