公开(公告)号：US20220004896A1

公开(公告)日：2022-01-06

申请号：US16919690

申请日：2020-07-02

Applicant: Oath Inc.

Inventor： Rina Leibovits ,  Oren Somekh ,  Yohay Kaplan ,  Yair Koren

IPC: G06N5/04 ,  G06N20/00

Abstract: The present teaching relates to method, system, and computer programming product for dynamic vector allocation. Machine learning is conducted using training data constructed based on a target vector having a plurality of feature entries, wherein each of the plurality of feature entries is mapped from at least one original attribute from one or more original source vectors. A feature entry in the target vector is identified based on a first criterion associated with an assessment of the machine learning, for replacing the corresponding at least one original attribute from the one or more original source vectors. At least one alternative attribute from alternative source vectors based on a second criterion is determined, wherein the at least one alternative attribute is to be mapped to the feature entry of the target vector. The feature entry of the target vector is populated based on the at least one alternative attribute.