Nearest Neighbor Search (NNS) is a fundamental problem in data structures with wide-ranging applications, such as web search, recommendation systems, and, more recently, retrieval-augmented ...
ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. The discovery of functional small molecules, chemical matter ...
Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...
Nearest neighbour classification techniques, particularly the k‐nearest neighbour (kNN) algorithm, have long been valued for their simplicity and effectiveness in pattern recognition and data ...
When you log onto LinkedIn, you’re normally presented with suggestions to connect with people you know, either because you went to the same university as them, or worked in the same company or ...
Abstract: In this study, the machine learning algorithm, K-Nearest Neighbor (KNN) is introduced for human action recognition. A wearable sensor is employed to collect the acceleration signals, which ...
Abstract: The purpose of this research is the development of an online learning system by the application of nearest neighbor algorithm for providing adaptive learning materials on the course of ...
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