User-centric optimization for interactive dictionary expansion

    公开(公告)号:US11645461B2

    公开(公告)日:2023-05-09

    申请号:US16786242

    申请日:2020-02-10

    CPC分类号: G06F40/242 G06F16/367

    摘要: A method is provided for dictionary expansion. The method acquires an object from a user and adds the object to a set of objects previously acquired from the user that form an expandable dictionary. The method calculates a centroid based on the set. The method calculates a similarity score of each of a plurality of objects relative to the centroid for each of a plurality of object features to calculate a weighted sum of similarity scores for each of the plurality of objects. The method presents candidate objects selected among the plurality of objects based on the weighted sum. The method acquires, from the user, a preferred candidate object among the candidate objects. The method updates weights of the plurality of features to maximize the weighed sum of similarity scores for the preferred candidate object. The method expands the dictionary by adding the preferred candidate object to the expandable dictionary.

    DATA AUGMENTATION BASED ON FAILURE CASES

    公开(公告)号:US20230027777A1

    公开(公告)日:2023-01-26

    申请号:US17372037

    申请日:2021-07-09

    IPC分类号: G06F11/36 G06K9/62

    摘要: A computer-implemented method is provided for data augmentation. The method includes receiving a set of different base models already pretrained and a set of different test cases. The method further includes collecting a plurality of prediction results of the set of different test cases from the set of different base models. The method also includes identifying a test case as a candidate for the data augmentation based on a number of models in the set of different base models which fail to solve the test case. The method additionally includes augmenting, by a processor device, the identified test case with additional data to form an augmented training dataset. The method further includes retraining at least some of the different base models with the augmented training dataset.

    Data augmentation based on failure cases

    公开(公告)号:US11797425B2

    公开(公告)日:2023-10-24

    申请号:US17372037

    申请日:2021-07-09

    IPC分类号: G06F11/36 G06F18/214

    摘要: A computer-implemented method is provided for data augmentation. The method includes receiving a set of different base models already pretrained and a set of different test cases. The method further includes collecting a plurality of prediction results of the set of different test cases from the set of different base models. The method also includes identifying a test case as a candidate for the data augmentation based on a number of models in the set of different base models which fail to solve the test case. The method additionally includes augmenting, by a processor device, the identified test case with additional data to form an augmented training dataset. The method further includes retraining at least some of the different base models with the augmented training dataset.