公开(公告)号：US20240320538A1

公开(公告)日：2024-09-26

申请号：US18123673

申请日：2023-03-20

Applicant: ADOBE INC.

Inventor： Ramasuri NARAYANAM ,  Shiv Kumar SAINI ,  Koyel MUKHERJEE ,  Manisha PADALA ,  Keshav VADREVU ,  Gautam CHOUDHARY ,  Atharv TYAGI

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Systems and methods identify anomalous data in tabular data. A set of tabular data records is received. Each tabular data record includes data elements for a numbers of attributes, with each data element providing a value for a corresponding attribute. An anomaly score is generated for each data element of each tabular data record. Additionally, an evidence set is defined for each attribute and each tabular data record based on the anomaly scores for the data elements. An anomaly score is generated for each attribute and each tabular data record using the evidence sets. An output is provided that identifies one or more anomalous data subsets determined based on the anomaly scores for the attributes and tabular data records. Each anomalous data subset identifies a subset of attributes and a subset of tabular data records.

公开(公告)号：US20250005075A1

公开(公告)日：2025-01-02

申请号：US18342474

申请日：2023-06-27

Applicant: Adobe Inc.

Inventor： Sachin Kumar Chauhan ,  Subrata MITRA ,  Sunav CHOUDHARY ,  Ramasuri NARAYANAM ,  Koyel MUKHERJEE ,  Gautam Pratap KOWSHIK

IPC: G06F16/901

Abstract: Tabular data is received. A graph is created based on the tabular data. The graph comprises nodes corresponding to key-value pairs of the tabular data. Weights are assigned to the nodes and to edges that connect the nodes. The node and edge weights are updated using a message-passing neural network (MPNN) framework. The resulting graph is sampled based on the updated weights.