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A Novel L-Fuzzy Concept Learning via Two-Way Concept-Cognitive Learning and Residuated Implication
Concept-cognitive learning (CCL) has been an active topic in artificial intelligence and cognitive computing. Two-way concept-cognitive learning...
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Transfer and online learning for IP maliciousness prediction in a concept drift scenario
Determining the maliciousness of a cybersecurity incident is essential to establish effective measures against it. To process large volumes of data...
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Unsupervised domain adaptation by incremental learning for concept drifting data streams
Incremental learning is a learning paradigm in which a model is updated continuously as new data becomes available, and its main challenge is to...
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ExeVis: concept-based visualization of exercises in online learning
AbstractIn recent years, online learning has gained popularity and proven to be an effective way of education. Numerous studies have analyzed...
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Concept learning consistency under three-way decision paradigm
Concept Mining is one of the main challenges both in Cognitive Computing and in Machine Learning. The ongoing improvement of solutions to address...
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Concept-Based Label Distribution Learning for Text Classification
Text classification is a crucial task in data mining and artificial intelligence. In recent years, deep learning-based text classification methods...
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Application Research of Multi-label Learning Under Concept Drift
In order to address the interference of concept drift on the results of multi-label learning algorithms, a hybrid kernel extreme learning machine is...
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Stability analysis of incremental concept tree for concept cognitive learning
Incremental concept cognitive learning is an emerging active issue that concerning incremental concept learning and dynamic knowledge processing in...
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Learning Factory Concept Tailored for Engineering Programmes for Underserved Communities
Access to learning factories for underserved persons is challenging, including limited access to design tools, innovative manufacturing methods, and...
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A Novel Method for Smart Fire Detection Using Acoustic Measurements and Machine Learning: Proof of Concept
Fires are a major hazard resulting in high monetary costs, personal suffering, and irreplaceable losses. The consequences of a fire can be mitigated...
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The concept information of graph granule with application to knowledge graph embedding
Knowledge graph embedding (KGE) has become one of the most effective methods for the numerical representation of entities and their relations in...
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Scalable concept drift adaptation for stream data mining
Stream data mining aims to handle the continuous and ongoing generation of data flows (e.g. weather, stock and traffic data), which often encounters...
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A novel approach to concept-cognitive learning in interval-valued formal contexts: a granular computing viewpoint
Concept-cognitive learning (CCL) is to make machines like human beings have the ability of summarizing and reasoning. Automatically learn and find...
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Fuzzy Semantic Classification of Multi-Domain E-Learning Concept
Scholarly articles are a great source of knowledge. Learning from them like E-learning requires automatic approaches to build concept-maps, learning...
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Participative Learning Experience Design Through Group Concept Map**
Although there has been an increasing amount of literature on learning experience design in the past five years, it is not clear yet how to...
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CDA-PDDWE: Concept Drift-Aware Performance-Based Diversified Dynamic Weighted Ensemble for Non-stationary Environments
Over the past decades, technological advancements have included the production of a huge number of data streams. Data streams comprise large amounts...
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Does giving students feedback on their concept maps through an on-screen avatar or a humanoid robot make a difference?
Active or engaged learning is often seen as a way to improve students’ performance concerning STEM topics. When following such a form of...
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Biologicalisation in Learning Factories – Learning Concept and Lab-Demonstrator for Bio-Fluids for Metal Processing
New technologies and concepts are continuously introduced in production engineering to get closer to the goal of sustainability. However, the skill...
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Continuous detection of concept drift in industrial cyber-physical systems using closed loop incremental machine learning
The embedded, computational and cloud elements of industrial cyber physical systems (CPS) generate large volumes of data at high velocity to support...
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Online rule fusion model based on formal concept analysis
A rule is an effective representation of knowledge in formal concept analysis (FCA), which can express the relations between concepts. One of the...
