Written by Abstract: Semantic search, which aims to understand the meaning and context of queries rather than simply matching keywords, has gained significant attention in recent years. As the volume of data continues to grow exponentially, the ability to perform semantic search efficiently over large-scale datasets becomes crucial. The increasing volume of data has amplified the critical need … Continue reading “Efficient Indexing Techniques for Large-Scale Semantic Search”
Abstract: Natural Language Processing (NLP) aims to enable computers to understand and process human language. A crucial aspect of this is the ability to represent the meaning of text and perform reasoning over it. This paper explores the landscape of meaning representation techniques in NLP, encompassing both symbolic and distributional approaches. We examine the methods … Continue reading “Meaning Representation and Reasoning in Natural Language Processing”
Abstract: The semantic interpretation of “things” – encompassing physical objects, abstract concepts, and everything in between – is a fundamental problem in artificial intelligence and cognitive science. Its broad, context-dependent usage requires systems to navigate the fluid boundaries between concrete and abstract entities, often relying on ontologies, reference resolution, and common sense reasoning to make sense … Continue reading “Semantic Interpretation of Things:”