Publication | Open Access
Milvus
262
Citations
29
References
2021
Year
Unknown Venue
EngineeringMachine LearningMachine Learning ToolSupport Vector MachineData ScienceData MiningLarge-scale DataManagementData IntegrationBig DataData Pre-processingData ManagementVector DataFeature EngineeringKnowledge DiscoveryComputer ScienceFeature ConstructionDynamic Vector DataData Modeling
Recently, there has been a pressing need to manage high-dimensional vector data in data science and AI applications. This trend is fueled by the proliferation of unstructured data and machine learning (ML), where ML models usually transform unstructured data into feature vectors for data analytics, e.g., product recommendation. Existing systems and algorithms for managing vector data have two limitations: (1) They incur serious performance issue when handling large-scale and dynamic vector data; and (2) They provide limited functionalities that cannot meet the requirements of versatile applications.
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