[ad_1] Introduction: Answer set programming (ASP) is a declarative programming paradigm that has gained popularity in recent years for solving complex computational problems. Unlike traditional imperative programming languages, ASP allows users to specify the desired…
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[ad_1] Introduction Commonsense reasoning is a fundamental aspect of human cognition that allows individuals to make inferences, draw conclusions, and navigate the complexities of everyday life based on a set of shared beliefs and assumptions.…
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[ad_1] Introduction: In recent years, Knowledge base question answering has become an essential tool for retrieving information from large scale databases. With the increasing amount of data available on the internet, traditional keyword-based search engines…
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[ad_1] Introduction Semantic web technology has emerged as a promising solution for organizing and extracting knowledge from the vast amount of information available on the internet. By using standardized metadata and ontologies, the semantic web…
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[ad_1] Introduction: Knowledge graphs have emerged as a powerful tool for representing structured knowledge in a variety of domains. These graphs provide a flexible and scalable way to capture relationships between entities and concepts, making…
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[ad_1] Introduction Graph generative models have gained significant attention in recent years due to their ability to synthesize graph structures with desired properties. These models have various applications in fields such as social network analysis,…
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[ad_1] Introduction Modular neural networks have been gaining attention in recent years due to their ability to enhance compositionality in neural networks. Compositionality refers to the capacity of a system to combine simpler components to…
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[ad_1] Introduction: In the era of big data, the continuous growth of networks such as social networks, communication networks, and the Internet of Things (IoT) has posed significant challenges for traditional machine learning algorithms. Traditional…
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[ad_1] Introduction Continual learning is a key concept in the field of artificial intelligence and machine learning, emphasizing the ability of a system to adapt and learn continuously from new data and experiences in order…
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[ad_1] Introduction Federated learning is a decentralized machine learning approach that allows multiple parties to collaboratively train a global model without sharing their data. This approach addresses privacy concerns and data security issues associated with…
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