Id Analytics, Inc.

Servicenow, Inc.

Symantec Corporation

Tao Hong

Xuhui Shao

Allen P Jost

Jianjun Xie

Baskar Jayaraman

Ted E Dunning

Stephen V Coggeshall

Chitrabharathi Ganapathy

Alan Tsang

Christer J DiChiara

Mike Cook

Rohit Lobo

Joe Blue

A document is received. The document is analyzed to discover text and structures of content included in the document. A result of the analysis is used to determine intermediate text representations of segments of the content included in the document, wherein at least one of the intermediate text representations includes an added text encoding the discovered structure of the corresponding content segment within a structural layout of the document. The intermediate text representations are used as an input to a machine learning model to extract information of interest in the document. One or more structured records of the extracted information of interest are created.

Determination of intermediate representations of discovered document structures

The present disclosure includes analyzing client instance performance trends to predict future client instance performance and adjusting thresholds used to send resource utilization alerts based on analyzing the client instance performance trends. In particular, a data center providing a platform as a service includes a database that stores performance data associated with client instances. The data center also includes alignment logic that temporally aligns the performance data, and a frequency based filter that compresses the aligned performance data based on frequency of values. The data center further includes dynamic threshold adjustment logic that adjusts thresholds associated with sending performance trend alerts based on analyzing the compressed set of performance data. In this manner, the thresholds may be dynamically adjusted for changing circumstances and/or relevant details associated with resource usage, and thus may more accurately send performance trend alerts indicative of situations when resource utilization becomes high and resources become low.

Dynamic threshold adjustment based on performance trend data

A method for determining a likelihood of fraud associated with an input identity record is disclosed herein. The disclosed method contemplates determining characteristics of the input identity record by examining content of one or more fields of the input identity record. Historical identity records related to the input identity record may then be retrieved so as to define a set of linked identity records. The method further includes computing one or more network-based features of the set of linked identity records. A fraud score may then be generated based upon the characteristics of the input identity record and the one or more network-based features.

System and method for identity-based fraud detection

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

System and method for identity-based fraud detection using a plurality of historical identity records

System and method for identity-based fraud detection through graph anomaly detection

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

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San Diego, CA, United States of America

Tao Hong