Paypal, Inc.

Harish Nalagandla

Srinivasan Manoharan

Vinesh Chirakkil

Gurinder Grewal

Sahil Dahiya

Christopher S Purdum

Girish Sharma

Jun Zhu

Yuehao Wu

Venkata Ramana Nadimpalli

Vahini Pobbathi

Ming Zhu

Jinwoo Lee

Ajay Aswal

Jian Wan

Deepak Raman

Amit Pandey

Vinaykanth Manthena

Methods and systems for using machine learning to automatically determine a data loading configuration for a computer-based rule engine are presented. The computer-based rule engine is configured to use rules to evaluate incoming transaction requests. Data of various data types may be required by the rule engine when evaluating the incoming transaction requests. The data loading configuration specifies pre-loading data associated with at least a first data type and lazy-loading data associated with at least a second data type. Statistical data such as use rates and loading times associated with the various data types may be supplied to a machine learning module to determine a particular loading configuration for the various data types. The computer-based rule engine then loads data according to the data loading configuration when evaluating a subsequent transaction request.

Self learning data loading optimization for a rule engine

Methods and systems are presented for providing automated online chat assistance in multiple languages. A query in a first language is received via a chat robot from a user device. The query is machine-translated into a second language and transmitted to an artificial intelligence system that includes a dialog tree configured in the second language. The artificial intelligence system determines a response in the second language to the query by locating a node corresponding to an intent based on the query in the dialog tree. The node includes a node ID and response text in the second language. The artificial intelligence system transmits the second-language response including the node ID to the chat robot. The second-language response is intercepted, and first-language response text corresponding to the second-language response text is determined based on the node ID. The second-language response text is then provided to the user device by the chat robot.

Systems and methods for providing multilingual support in an automated online chat system

Techniques are disclosed relating to transitioning between data stores using a data migration server. In some embodiments, the data migration server may be used to access data stored on a preexisting data store to service requests from a plurality of services. A dual-write operation mode for the data migration server may then be enabled such that, in response to a given write request, the data migration server writes a given data entry to both the preexisting data store and a replacement data store. Further, a dual-read operation mode may be enabled such that, in response to a given read request, the data migration server reads a corresponding data entry from both the preexisting and replacement data stores. Configuration settings for the data migration server may then be adjusted to designate the replacement data store as the primary data store to service requests from the services.

Data store transition using a data migration server

Methods and systems for automatically discovering data types required by a computer-based rule engine for evaluating a transaction request are presented. Multiple potential paths for evaluating the transaction request according to the rule engine are determined. An abstract syntax tree may be generated based on the rule engine to determine the multiple potential paths. Based on an initial set of data extracted from the transaction request, one or more potential paths that are determined to be irrelevant to evaluating the transaction request are identified. Types of data required to evaluate the transaction request according to the remaining potential paths are determined. Only data that corresponds to the determined types of data is retrieved to evaluate the transaction request.

Automatic discovery of data required by a rule engine

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San Jose, CA, United States of America

Harish Nalagandla