METHOD AND APPARATUS FOR VECTOR RETRIEVAL, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20240370485A1

    公开(公告)日:2024-11-07

    申请号:US18748078

    申请日:2024-06-19

    Abstract: The present disclosure provides a vector retrieval method and apparatus, a device and a medium, and relates to the field of artificial intelligence technologies, particularly the fields of cloud computing technologies, big data technologies, or the like. The vector retrieval method includes: acquiring a plurality of candidate vector indexes generated in advance, the plurality of candidate vector indexes being generated based on a plurality of candidate field values included in a target field of original data; acquiring a query vector and a filter condition, the filter condition being used for indicating a condition required to be satisfied by a target vector corresponding to the query vector; if the filter condition includes a target field value required to be satisfied by the target field, determining a target vector index corresponding to the target field value in the plurality of candidate vector indexes; and performing query in the target vector index based on the query vector to obtain the target vector.

    METHOD AND APPARATUS FOR GENERATING INDEX, AND ELECTRONIC DEVICE

    公开(公告)号:US20250013620A1

    公开(公告)日:2025-01-09

    申请号:US18748362

    申请日:2024-06-20

    Abstract: A method for generating an index, and an electronic device are provided. The detailed solution includes: determining a first parameter group and a second parameter group in response to receiving a query request for a first vector database and there being no available index for the first vector database, constructing a first index for the first vector database based on the first parameter group, and querying the first vector database based on the first index; constructing a second index for the first vector database based on the second parameter group in response to meeting a preset condition; and in response to determining that construction of the second index is completed, deleting the first index, and querying the first vector database based on the second index.

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