International Business Machines Corporation

American Express Travel Related Services Company, Inc.

Conduent Business Services, LLC

Rahul Ghosh

Aaron J Quirk

Upendra Sharma

Giribabu V Paramkusham

Lin Sun

Hugh Edward Hockett

Corville O Allen

Bernadette Alexia Carter

Ravi Krishnan Muthukrishnan

Joseph N Kozhaya

Xianjun Zhu

Ivan M Heninger

Douglas Alan Larson

Krishnaprasad Narayanan

William R LaRiccia

Shouvik Mitra

Al Chakra

Rohith Kottamangalam Ashok

Roy Frank Brabson

Shourya Roy

Koustuv Dasgupta

Arindam Chatterjee

Stuart J Reece

Nitish Sharma

Edward Raymond Bernal

Rocky D McMahan

James Patrick Robbins

Pratap Singh Rathore

Brian C Rosenfield

Xian Jun Zhu

David N Nguyen

Drew Hoover Sternesky

William R Lariccia

Vasanth Raghavan

Dana Lea Price

Murthy V Devarakonda

Vijay Krishnarao Naik

Atul Singh

Saju Mathew

Jose A Nativio

Ajith Ramanath

Anirban Mondal

Avantika Gupta

Bobby Chetal

Ansuman Banerjee

Anshul Jain

Varun Sharma

Ashish Garg

Lawrence E Clark

Soumi Chattopadhyay

Swetha P Srinivasan

Varun Agarwal

Ashni Jauhary

At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

Computer-based systems for management of big data development platforms based on machine learning techniques and methods of use thereof

At least some embodiments are directed to an insights inference system that produces multiple insights associated with an entity. The insights inference system generates a decision tree machine learning model, assigning a first insight to a parent node of a decision tree machine learning model and assigning at least one second insight to child nodes of the decision tree machine learning model. Each child node is associated with a sequence number and a rank number. The sequence number and the rank number are indicative of a significance associated with the at least one second insight. The insight inference system responds to queries by traversing the decision tree machine learning model to compute at least one response insight based on the sequence number and the rank number associated with each child node and outputs the at least one response insight to a client terminal.

Computer-based systems having computer engines and data structures configured for machine learning data insight prediction and methods of use thereof

Embodiments of the present disclosure disclose methods and systems for generating operational alarms for a plurality of clients, the operational alarms being generated by a business performance system, each client being associated with a plurality of Key Performance Indicators (KPIs). An aggregate rank for each client based on ranks of each KPI is generated. For each client: the aggregate rank of the client over one or more time periods is monitored. If the aggregate rank deteriorates over the one or more time periods, a severity indicator is determined based on change of value of each KPI and change of rank of each KPI for the client over the one or more time periods. An operational alarm based on value of the severity indicator is determined. The operational alarm is displayed on a user interface, wherein the operational alarm displays one or more KPIs with highest severity values.

Methods and systems for analyzing aggregate operational efficiency of business services

At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request via a proxy service to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

A technique for caching evidence for answering questions in a cache memory of a data processing system (that is configured to answer questions) includes receiving a first question. The first question is analyzed to identify a first set of characteristics of the first question. A first set of evidence for answering the first question is loaded into the cache memory. A second question is received. The second question is analyzed to identify a second set of characteristics of the second question. A portion of the first set of evidence, whose expected usage in answering the second question is below a determined threshold, is unloaded from the cache memory.

Managing data in a cache memory of a question answering system

Techniques for managing data in a cache memory of a question answering system

A method, system and computer program product for selecting virtual machines to be migrated to a public cloud. The current resource usage for virtual machine instances running in the private cloud is determined. Furthermore, any scaling policies attached to the virtual machine instances running in the private cloud are obtained. Additional resource usages for any of the virtual machine instances with a scaling policy are computed for when these virtual machine instances are scaled out. A cost of running a virtual machine instance in the public cloud is then determined using its current resource usage as well as any additional resource usage if a scaling policy is attached to the virtual machine instance based on the cost for running virtual machine instances in a public cloud. If the cost is less than a threshold cost, then the virtual machine instance is selected to be migrated to the public cloud.

Selecting virtual machines to be migrated to public cloud during cloud bursting based on resource usage and scaling policies

A computer-implemented method for deploying a plurality of data conversion flow between a first application in a first system to a second application in a second system, without restarting the plurality of data conversation flow, is provided. The computer-implemented method may further include providing a plurality of modifiable data conversation that identifies a plurality of input parameters, a plurality of data formats, a plurality of data description, a plurality of conversation routines, a plurality of paths of the conversion routines, and a plurality of output information that determines routes of converted data for the first application. The computer-implemented method may further include converting the plurality of modifiable data conversion to form a data input from the first application to the second application. The computer-implemented method may further include providing an application interface for transmitting the plurality of modifiable data to the second application, without restarting the data conversion flow.

Reusable message flow between applications of a message broker integrated systems environment

A management system receives inputs over a period of time from outputs of one or more sensors placed within a proximity to a service area, the one or more sensors for detecting at least one of at least one weight and at least one sound. The management system dynamically estimating, based on a rate of a percentage of change of the at least one weight over the period of time and types of sounds of the at least one sound for the service area, one or more wait times until a completion of use of the service area. The management system dynamically generating one or more wait time estimates in real time for the service area based on the one or more wait times and a current number of users waiting in a queue for the service area.

Real-time wait estimation and prediction via embedded sensors

According to one aspect of the present disclosure a system and technique for dynamic system level agreement provisioning includes: a computing environment configured with allocatable computing resources; and a host having a processor unit operable to execute a service level agreement (SLA) module. The SLA module is configured to: identify service level criteria for a customer of computing services of the computing environment; determine characteristics of the computing environment; identify a time period for providing the computing services; evaluate one or more utility functions defining service level variables; and automatically determine a service level agreement (SLA) provision for the customer based on the one or more utility functions.

Dynamic system level agreement provisioning

According to one aspect of the present disclosure a method and technique for dynamic system level agreement provisioning is disclosed. The method includes: identifying, by a data processing system of a computing environment service provider, service level criteria for a customer of computing services; determining characteristics of the computing environment; identifying a time period for providing the computing services; evaluating one or more utility functions defining service level variables; and automatically determining, by the data processing system, a service level agreement (SLA) provision for the customer based on the one or more utility functions.

In some aspects, a computer-implemented method for diagnosing an unfavorable mobile application user experience is described. The method may include retrieving user application interaction data from a mobile device, inter-correlating the user application interaction data, updating a user interaction database with the inter-correlated user application data, and diagnosing, via a processor operatively connected to the user interaction database, information indicative of a cause of the unfavorable user experience.

System and method for diagnosing an unfavorable mobile application user experience

A method is provided for building patterns with high level pattern topology requirements for deployment across multiple systems. The patterns are built based on pattern capabilities and configurations of the multiple systems. Such patterns can meet the desired pattern capabilities including high availability and/or continuous capabilities.

Domain-specific pattern design

In one aspect, a computer-implemented method for compressing content based on a social factor, an environmental factor, and a relational factor is described. The method may include monitoring access to the content, forming, by a processor, a contextual evaluation based on the monitored access and determining an importance of the content based on the contextual evaluation. The method may further include storing the content in a compressed form, where the compressed form is selected based on the importance.

Dynamic compression of multimedia content based on social and relational context

Growing community of inventors

Morrisville, NC, United States of America

Rahul Ghosh